Source-selection based Internet backbone traffic shaping

ABSTRACT

Source-selection based Internet backbone traffic shaping, including the steps of assessing a large number of network paths through which erasure-coded fragments usually flow when transmitted from a large number of relevant fractional-storage CDN servers to an assembling device; accessing preferences for fragment delivery via many of the paths; and selecting the servers whose assessed paths fit well the preferences for fragment delivery to the assembling device. Wherein the servers are accessed via the Internet, not all servers are connected to the Internet via the same networks, and the erasure-coded fragments are encoded with a redundancy factor greater than one from contents.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 61/105,683, filed Oct. 15, 2008, and U.S. ProvisionalPatent Application No. 61,251,437, filed Oct. 14, 2009.

BACKGROUND

The Internet is a global system of interconnected computer networks. Oneor more of the networks may be congested when a large volume of data isbeing routed over inadequate communication links or across high latencynetworks that cannot handle the large volume of data. The result is aslowing down of packet movement, packet loss and a drop in servicequality. Therefore, in some cases it is desirable to avoid usingcongested communication links and/or networks.

BRIEF SUMMARY

In one embodiment, a content delivery system, comprising: several groupscomprising fractional-storage CDN servers configured to storeerasure-coded fragments associated with contents; the groups areconnected to the Internet via Internet backbone tier one networks,wherein not all groups are connected via the same networks; and a verylarge number of assembling devices configured to obtain fragments fromsub-sets of the servers; wherein the system has a meaningful effect onthe traffic transported via at least one Internet backbone tier onenetwork by determining the sub-sets.

In one embodiment, a method for shaping traffic, comprising: assessing alarge number of network paths through which erasure-coded fragmentsusually flow when transmitted from a large number of relevantfractional-storage CDN servers to an assembling device; accessingpreferences for fragment delivery via many of the paths; and selectingthe servers whose assessed paths fit well the preferences for fragmentdelivery to the assembling device; wherein the servers are accessed viathe Internet, not all servers are connected to the Internet via the samenetworks, and the erasure-coded fragments are encoded from contents andsupport source-selection diversity.

In one embodiment, a content delivery system, comprising: a large numberof fractional-storage CDN servers, assembling devices, and a managingcomponent; the servers are topologically dispersed across differentInternet networks and are configured to store erasure-coded fragmentsassociated with contents; the assembling devices are configured toobtain fragments from the servers; and the managing component isconfigured to significantly affect the fragment traffic transported viaat least one Internet backbone router by influencing selections offragment delivering servers.

Implementations of the disclosed embodiments involve performing orcompleting selected tasks or steps manually, semi-automatically, fullyautomatically, and/or a combination thereof. Moreover, depending uponactual instrumentation and/or equipment used for implementing thedisclosed embodiments, several embodiments could be achieved byhardware, by software, by firmware, or a combination thereof. Inparticular, with hardware, embodiments of the invention could exist byvariations in the physical structure. Additionally, or alternatively,with software, selected functions of the invention could be performed bya data processor, such as a computing platform, executing softwareinstructions or protocols using any suitable computer operating system.Moreover, features of the embodiments may be combined.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments are herein described, by way of example only, withreference to the accompanying drawings. No attempt is made to showstructural details of the embodiments in more detail than is necessaryfor a fundamental understanding of the embodiments. In the drawings:

FIG. 1 illustrates geographically distributed fractional-storageservers.

FIG. 2 to FIG. 4 illustrate the influence of selecting source servers onbackbone traffic.

FIG. 5 illustrates server selection for network path determination.

FIG. 6 is a flow diagram of one method in accordance with oneembodiment.

FIG. 7 illustrates different loads at different times for different timezones.

FIG. 8 illustrates peak-to-average traffic ratios generated byassembling devices distributed over different time zones.

FIG. 9 illustrates US-based fractional-storage servers deliveringerasure-coded fragments to assembling devices spread over the globe.

FIG. 10 illustrates data centers communicating via shared links.

FIG. 11 illustrates fractional-storage servers communicating via sharednetworks.

FIG. 12 illustrates an assembling device obtaining erasure-codedfragments from fractional-storage servers.

FIG. 13 illustrates a stand-alone content delivery server.

FIG. 14 illustrates real time fragment retrieval, segmentreconstruction, and content presentation.

FIG. 15 illustrates real time fragment retrieval in random order.

FIG. 16 illustrates fractional-storage servers having the same bandwidthcapability.

FIG. 17 illustrates fractional-storage servers having differentbandwidth capabilities.

FIG. 18 and FIG. 19 illustrate a case where a fractional-storage serverhas failed.

FIG. 20 illustrates a server failure due to network congestion.

FIG. 21 illustrates retrieving fragments according to locality.

FIG. 22 illustrates distribution and storage of erasure-coded fragmentson fractional-storage servers.

FIG. 23 illustrates three examples of changes made to redundancy factorsaccording to changes in demand.

FIG. 24 illustrates a broadcast-like effect.

FIG. 25 to FIG. 27 illustrate changes in content consumption.

FIG. 28 illustrates utilization of the entire aggregated bandwidth offractional-storage servers for multiple content delivery.

FIG. 29 and FIG. 30 illustrate generation of a larger quantity oferasure-coded fragments near fast start points.

FIG. 31 and FIG. 32 illustrate different embodiments of contentsegmentation.

FIG. 33 illustrates operation of hybrid pull and push protocols.

FIG. 34 illustrates fast real time fragment retrieval.

FIG. 35 illustrates one embodiment of a fragment pull protocol.

FIG. 36 illustrates fractional-storage servers placed at differentlocations.

FIG. 37 to FIG. 39 illustrate one embodiment where a data center hostingfractional-storage servers has failed and is replaced by a differentdata center.

FIG. 40 and FIG. 41 illustrate operation of multi data-center CDN.

FIG. 42 illustrates one embodiment of segmenting content, encoding thesegments into erasure-coded fragments, distributing the fragments tofractional-storage servers, and obtaining the fragments by assemblingdevices and assembling servers.

FIG. 43 illustrates assembling content utilizing a proxy server.

FIG. 44 illustrates fractional-storage servers located on the Internetbackbone.

FIG. 45 illustrates an assembling server located at a network juncture.

FIG. 46 illustrates a server array managing a pool of bandwidthamplification devices.

FIG. 47 illustrates a hybrid Servers-P2P system.

DETAILED DESCRIPTION

FIG. 1 illustrates one example of geographically distributedfractional-storage servers 399 a to 399 n, in which servers 399 a to 399c are located in Europe 676, servers 399 d to 399 g are located on theeast coast of the US 677, servers 399 h to 399 i are located on the westcoast of the US 678 and servers 399 k to 399 n are located in Japan 679.The fractional-storage servers store erasure-coded fragments. Theerasure-coded fragments are associated with segments of content, whichmay be streaming content. Assembling devices all over the world obtainerasure-coded fragments from the globally distributed fractional-storageservers and optionally decoded the fragments to reconstruct thesegments. The characteristics of the fractional-storage system,according to some embodiments, allow the globally distributed assemblingdevices to exploit the outgoing bandwidth of the globally distributedfractional-storage servers approximately up to the point where allservers 399 a to 399 n utilize their available outgoing bandwidth forcontent delivery.

In one embodiment, the main demand for fragments shifts between thedifferent global locations as the day elapses. For example, at 8 pmPacific Standard Time, the main fragment demand is generated from the USwest coast. At that time, the local time in the east coast is lateevening, the time in Europe and Japan is early morning and noonrespectively, and thus very little fragment demand is generated fromthese regions. The high fragment demand load generated from the westcoast is spread across all of the fractional-storage servers. As the dayelapses, the load generated from the west coast declines, and the mainload shifts to Japan as time there becomes afternoon. When that happens,the servers are still able to supply all content demands, as they arestill able to deliver maximal bandwidth to assembling devices in Japan.As the cycle continues, the main load shifts again from Japan to Europe,from Europe to the US east coast, and from there back to the US westcoast, following a 24-hour cycle. In some embodiments, the servers areable to deliver maximal fragment traffic, resulting from peak demandsoccurring during a day cycle, to anywhere on the globe.

In one example, there are 14 globally distributed fractional-storageservers; each server has a bandwidth of B, and the total capacity of thearray is 14×B. Assuming the total global peak demand during the dailycycle does not exceed Bg, then the system is balanced and can meet alldemands during the daily cycle if Bg<14×B, meaning that B>Bg/14. In thisexample, all servers may be at, or may approach, their peak bandwidthcapabilities for a relatively long period, and feature relatively shortidle periods. In one example, the number of servers in the global arrayis 10,000, from which 2,500 are located on the US west coast, 2,500 onthe east coast, 2,500 in Europe and 2,500 in Japan. In one example, thenumber of servers in the global array is 1,000, from which 100 arelocated on the west coast, 700 on the east coast, 100 in Europe and 100in Japan.

In one embodiment, multiple contents originating from multiple globallocations (and therefore expected to require high loads at differenttimes of day), are all stored on the globally distributedfractional-storage servers. Therefore, the system's bandwidth capacityequals the aggregated bandwidth of its server members, optionallyregardless of which content generates high load, regardless of when theload is generated during the day, and regardless of where the load isgenerated from.

In one embodiment, at some point in time, some portions of the Internetmay become congested at some global locations. The global system assuresthat servers not affected by the congestion handle the excess load, suchthat operation close to peak bandwidth performance is still possible.

In one embodiment, the selection of which fractional-storage serversdeliver erasure-coded fragments to which assembling devicesapproximately determines the network paths through which the fragmentsare transported. When the system has a redundancy factor greater than 1,there is a degree of freedom in selecting the servers that can deliver adecodable set of fragments to an assembling device. If the servers arespread over different networks, then each server, or groups of servers,may have different networks path through which fragments flow whentransmitted to an assembling device. Selecting the servers thereforemeans selecting network paths through which fragments are delivered toan assembling device. As the redundancy factor, the storage gain, andthe diversity at which servers are spread over different networksincrease, so does the number of potential network paths resulting fromserver selections. The selection of paths, via selection of servers, canbe used to avoid congested networks, to prefer certain paths that aremore cost effective, or to optimize any other criterion related tofragment flow paths.

FIG. 2 to FIG. 4 illustrate the influence of selecting source servers onbackbone traffic. FIG. 2 illustrates one example whereinfractional-storage servers 3599 a to 3599 j are grouped in threelocations 3541, 3542, and 3543, connected to the Internet via networks3505, 3402, and 3509 respectively. Assembling devices 3537, 3538, and3539 are connected to the Internet and obtain fragments from theservers. Assuming any three servers can be used to deliver decodablesets of fragments to the assembling devices, servers 3599 a, 3599 d, and3599 h are selected to deliver fragments to assembling device 3539. Inthis case, the resulting three network paths through which fragmentsflow to the assembling device are (i) from server 3599 a: first path3509, 3501, 3403 (ii) from server 3599 d: second path 3505, 3503, 3501,3403, and (iii) from server 3599 h: third path 3402, 3508, 3502, 3501,3403.

FIG. 3 illustrates one example wherein networks 3502, 3504, and 3508 getcongested with Internet traffic, not necessarily as a result of fragmenttraffic generated by servers 3599 a to 3599 j, and possibly as a resultof general Internet traffic. The third path includes two of thecongested networks: 3508 and 3502, and should therefore be avoided. Thismeans that another server, instead of 3599 h, has to be selected, suchthat it does not result in a fragment delivery path comprising networks3508 and 3502. Server 3599 b is therefore selected, resulting in afragment delivery path of 3509, 3501, 3403, which is similar to thefirst path already delivering fragments from server 3599 a. Assemblingdevice 3538 will use the servers 3599 h to 3599 j, as they are the onlyservers that avoid the congested networks. The path in this casecomprises networks 3402 and 3401. Assembling device 3537 can use anythree of the servers belonging to groups 3541 and 3543.

In one embodiment, the different networks are associated with differentcosts. The cost may be related to any of the following parameters, orother parameters relevant to transporting fragments over a network: (i)network's congestion level, (ii) network's remaining capacity, (iii)network's packet loss, (iv) network's latency, (v) network's latencyvariance, and/or (vi) the fee for transporting bits over the network. Inone example, selecting which servers deliver fragments to whichassembling devices is performed such that the resulting fragmentdelivery paths comprise networks having the least aggregated cost, or acompetitive aggregated cost compared to alternative paths. FIG. 4illustrates one example of assigning costs to network paths. Each of thenetworks is associated with a cost of 1 to 4. The higher the cost, themore congested the network. Assembling device 3539 can obtain fragmentsfrom either server group 3541, 3542, or 3543. The resulting three pathshave the following aggregated costs: (i) first path, from group 3543:4+1+1=6, (ii) second path, from group 3541: 3+1+1+1=6, (iii) and thirdpath, from group 3542: 1+2+2+1+1=7. The servers are selected from thefirst and second groups, as the resulting path cost is 6. Servers fromthe third group are usually not selected, as the resulting path cost is7.

FIG. 5 illustrates one embodiment wherein the selection of which serversdeliver fragments to which assembling devices is used to determinenetwork paths for fragment delivery. The servers are selected such thatthe resulting paths: (i) avoid certain loaded routers, and/or (ii)comprise routers having an aggregated cost lower than other possiblepaths. Fragment traffic going from groups of servers 3541, 3542, 3543 toan assembling device 3539 may pass through any of the routers 3501 to3506, depending on which three servers are selected for fragmenttransmission. In one example, router 3506 is congested. Therefore, onlyserves 3599 d to 3599 g and 3599 h to 3599 j are considered for fragmentdelivery, in order to avoid transporting the fragments via the congestedrouter 3506.

Network paths, networks, and/or routers, which should be avoided, may beidentified using one or more of the following embodiments. In oneembodiment, the operator/owner of the networks/routers indicates thatcertain networks/routers are to be avoided. In one embodiment, thenetworks/routers are associated with a cost that is used for selectingthe paths. In one embodiment, the different paths are empiricallychecked by transporting traffic from servers to assembling devices, andmeasuring parameters such as latency, latency variance, fragment orpacket loss, and/or traffic outages. In one embodiment, certainnetworks/routers are to be avoided during a certain period of the day,and can be used during another period of the day. For example, anInternet bandwidth provider has a high traffic load on one of itsnetwork links during the afternoon, but this same link is almost free oftraffic during the early morning. In this case, the provider canindicate that fragments can be delivered via the link only during earlymornings. In another example, an Internet backbone provider has a hightraffic load on one of its Tier-1 networks during the evenings, and amoderate load during the noon period. In this case, the process ofselecting the fragment delivering servers will consider this, and selectdelivery paths comprising the Tier-1 network only during the noonperiod.

In one embodiment, after obtaining some data regarding some of theloads, availabilities, losses, costs, preferences, and/or any other datathat may influence the selection of the servers, algorithms and/ortheorems such as Minimax (also known as Minmax) may be used foroptimizing the selections.

In some embodiments, the path though which a fragment will flow from aserver to an assembling device may be estimated using one or more of thefollowing: (i) TraceRoute functions to map routers between the variousservers and the assembling device, or (ii) obtaining a topological mapof the Internet, and estimating the paths accordingly. The estimatedpath may then be used to shape the actual fragment flow paths byselecting fragment-delivering servers. In one embodiment, the paththrough which fragment flow is unknown, and the determination of whichservers deliver fragments to which assembling devices is performedapproximately randomly, until an indication is received that a certainnetwork, or router, or groups of such, are avoided.

In one embodiment, the server selections are made by a managingcomponent that has access to network/router usage preferences, and toestimations of paths transporting fragments from servers to assemblingdevices. In one embodiment, the managing component functionality isintegrated in a control server or a managing server, which instructsassembling devices to use certain servers. In one embodiment, themanaging component resides within assembling devices.

FIG. 6 is a flow diagram illustrating one method for shaping traffic,comprising the following steps: In step 7390, assessing a large numberof network paths through which erasure-coded fragments usually flow whentransmitted from a large number of relevant fractional-storage CDNservers to an assembling device. In step 7391, accessing preferences forfragment delivery via many of the paths. And in step 7392, selecting theservers whose assessed paths fit well the preferences for fragmentdelivery to the assembling device; wherein the servers are accessed viathe Internet, not all servers are connected to the Internet via the samenetworks, and the erasure-coded fragments are encoded with a redundancyfactor >1 from contents. Optionally, at least some of the servers areconnected to the Internet via Internet backbone tier one networks.Optionally, the network paths consist essentially of tier one networks.Optionally, the network paths comprise many of the networks in the pathof a fragment delivered from a server to the assembling device.Optionally, the content is streaming content, the fragments aregenerated from approximately sequential segments of the content, and thefragments are delivered to the assembling device approximately accordingto the sequential order of the segments. Optionally, the number ofnetwork paths is at least 10, the number of relevant servers is at least20, and the storage gain of the servers in regard to an average contentis at least 10. Optionally, the preferences are a cost function, and thestep of selecting the servers comprises minimizing the cost function bydetermining which servers are to deliver fragments to the assemblingdevice. Optionally, the preferences for selecting a network path arebased on the accumulated costs of using the networks through which thepath passes, whereby a lower accumulated cost results in a higherpreference for the path. Optionally, the cost of delivering fragmentsvia a network is related to the traffic load on the network, whereby thehigher the traffic load on the network the higher the cost is, andwherein the load on the network is provided by the network operator.

In one embodiment, a user's cost on a globally distributedfractional-storage system is determined according to the correlationbetween the user's consumption profile and the system's load. Thesmaller the correlation, the lower the user's cost. In one embodiment,the cost of streaming content to a new user is calculated using thefollowing steps: receiving the locations of the user, the other users,and the CDN servers; estimating the time periods in which the new userwill consume its maximum BW; calculating the correlation between theuser's consumption and the current load; and pricing users who balancethe load significantly lower than users who consume content when thesystem is loaded.

In one embodiment, the servers are spread over different time zones.Different servers located at different time zones usually encounter peakload conditions at different times, especially if they share resources,such as communication link to the Internet, processing resources,storage, Tier-1 ISP networks, backbone networks, or any other resourceswith local servers delivering general Internet traffic. Load conditionsmay refer to actual load on the servers, load on a communications linkconnecting the server to the Internet, load on a local backbone orTier-1 network, or any type of condition in which additional fragmenttraffic will contribute to service degradation. In the case of a loadcondition, the system may refrain from obtaining fragments from serversthat directly contribute to the load, and try to obtain fragments fromservers that do not directly contribute to the load. Serversencountering load conditions below a certain threshold are usually foundsomewhere, as they are spread over different time zones, and theseservers may be the preferred fragment sources.

FIG. 7 illustrates one example of different loads at different times fordifferent time zones. Graphs 641 a, 641 b, 641 c and 641 d representload levels encountered by server groups 679, 676, 677 and 678respectively, located in the Far East, Europe, the US east coast, andthe US west coast respectively. In one example, the loads refer totraffic levels on communication links connecting the data centers, inwhich the servers are placed, to the Internet. In this case, the trafficmay be general Internet traffic generated by servers and otherapplication/s not necessarily related to fragment delivery, and thecommunication links can also be referred to as shared links, as they areused to transport both fragment traffic and general Internet traffic.During a 24-hour period, all encountered load levels complete one cycle.The load level graphs are shifted in time in respect to each other,according to the time shifts between the various time zones around theworld in which the different server groups are located. As an example,graph 641 a represents load encountered by the servers in the Far East,with a peak load occurring about 7 hours before graph 641 b representingload encountered by the servers in Europe.

At each arbitrary point in time, server groups around the world mayencounter different load conditions. As an example, at point 642 a,server group 679 encounters medium load conditions, server group 676encounters peak load conditions, and server groups 677 and 678 encounterlow load conditions. Therefore, at the point in time 642 a, it isbeneficial for assembling devices to obtain erasure-coded fragments onlyfrom server groups 677, 678, and maybe 679. Server group 676 encounterspeak load conditions, and therefore will not be approached by theassembling devices. At a different point in time 642 b, the worldwideload conditions change, such that server groups 679 and 676 encounterlow load conditions, and server groups 677 and 678 encounter high loadconditions. At this point, assembling devices will obtain fragments fromservers groups 679 and 676 and will refrain from approaching servergroups 677 and 678.

In one embodiment, the load conditions encountered by each server group,or by specific servers, are published by the servers. In one embodiment,the load condition level encountered by each server is sent to eachassembling device as a response to an erasure-coded fragment request.

In one embodiment, the communication link transporting fragments from aserver or group of servers to the Internet is owned by a data centeroperator. The data center operator publishes the load conditionassociated with the link. The published information is used to selectservers that transmit fragments via relatively unloaded links ascompared to other links.

In one embodiment, the load conditions encountered by a server aredetected by an outside source, such as an assembling device or a controlserver, using one of the following methods: (i) detecting an increasedlatency in responding to a request such as a fragment pull protocolrequest, (ii) detecting a certain level of latency variance, (iii)detecting a certain level of packet or fragment loss, and/or (iv)detecting outages in server's traffic.

FIG. 8 illustrates one embodiment in which assembling devicesdistributed over different time zones together induce fragment traffichaving a reduced peak-to-average traffic ratio, as compared to thefragment traffic induced by assembling devices located in any singletime zone. Graph 1602 illustrates the fragment traffic induced byassembling devices located at a first time zone. The peak of graph 1602occurs during the late afternoon, local time of the first time zone.Similarly, graphs 1603 and 1604 illustrate induced traffic from secondand third time zones. Since the first, second and third time zones aredifferent, the peak traffic of each graph occurs at a different time.The peak-to-average fragment traffic ratios of graphs 1602 to 1604 arerelatively high, since most of the traffic is generated close to thepeak demand. In the case of video traffic, a daily peak-to-averagetraffic ratio of about six is expected during one day, starting at T1and ending at T2. The combined traffic induced by all assembling devicesis the sum of graphs 1602 to 1604, which is schematically illustrated asgraph 1601. Since the peaks of graphs 1602 to 1604 occur at differenttimes, the combined traffic 1601 behaves much more smoothly and haspeaks close to the peaks of graphs 1602 to 1604, resulting in a muchlower peak-to-average traffic ratio, which in some embodiments is abouttwo or three. This means that the fractional-storage servers can beutilized during longer periods of the day when servicing assemblingdevices located at different time zones. In one embodiment, thedistribution of the assembling devices to the different time zonesresults in an approximately flat traffic during the day, having apeak-to-average traffic ratio approaching one. Such a distribution ischallenging in real life deployments, but can be approached byengineering the distribution of the assembling devices over the globe.

In one embodiment, the severs are connected to the Internet usingguaranteed fixed bandwidth communication links, and can together deliverto the Internet fragment traffic of 1610 all day. In this case, it isclear that traffic graph 1601 utilizes the fixed bandwidth capacity 1610better than any of the graphs 1602 to 1604, since it approaches themaximal capacity for longer periods over the day.

In one embodiment, the servers are spread over two or more continents,and some of the fragments associated with the same segments are storedon different servers located on different continents. This achievescontent placement diversity, and results in better immunity to differentnetwork and server faults.

FIG. 9 illustrates one embodiment in which US-based fractional-storageservers 399 a′ to 399 n′ deliver erasure-coded fragments to assemblingdevices spread over the globe. The assembling devices spread over theglobe induce a total fragment traffic from the US-based servers having areduced peak-to-average traffic ratio, as compared to the fragmenttraffic induced by assembling devices located in any single time zone.In one example, 5,000 fractional-storage servers are located in the USand service 10 million assembling device subscribers spread over theglobe. At a first period during the day, the servers delivererasure-coded fragments concurrently to 2 million assembling deviceslocated primarily in Japan. At a second period during the day, theservers deliver erasure-coded fragments concurrently to 2 millionassembling devices located primarily in Europe. At a third period duringthe day, the servers deliver erasure-coded fragments concurrently to 2.5million assembling devices located primarily on the East Coast, and ½million assembling devices located primarily on the West Coast. At afourth period during the day, the servers deliver erasure-codedfragments concurrently to ½ million assembling devices located primarilyon the East Coast, and 2.5 million assembling devices located primarilyon the West Coast. According to this example, the servers are capable ofdelivering a peak fragment traffic resulting from the demand of at least3 million assembling devices concurrently.

FIG. 10 illustrates one embodiment of data centers communicating viashared links. Fractional-storage servers 1699 a to 1699 c are collocatedwith at least one general server 1698 in a data center 1671. All theservers are connected to the Internet via a shared communication link1681. Therefore, erasure-coded fragment traffic transmitted by thefractional-storage servers and general Internet traffic transmitted bythe general server are mixed together on the shared link 1681.Similarly, fractional-storage servers 1699 d to 1699 g are collocatedwith at least one general server 1699 in a data center 1672, and sharethe same communication link 1682 to the Internet. In one embodiment, thefractional-storage servers are selected for fragment transmittal whenthe communication link through which they transmit fragments to theInternet is loaded below a certain level. This principle is demonstratedby the following example: assuming that any three fractional-storageservers out of 1699 a to 1699 g store a decodable set of fragments, thethree servers will be selected according to the load of the link throughwhich they communicate. If the general server 1698 transmits a highlevel Internet traffic via link 1681, and this traffic is close to themaximum capacity of the link, then using any of servers 1699 a to 1699 cis not advisable. Instead, in a case where the general server 1699 doesnot create a high level traffic and link 1682 is relatively free totransport fragments, any three servers out of servers 1699 d to 1699 gmay be used. When the fractional-storage servers deliver fragments tomany assembling devices, servers transmitting via relatively unloadedlinks are preferred, such that the end effect is that servers 1699 d to1699 g deliver a higher fragment load than servers 1699 a to 1699 c. Inother words, servers 1699 d to 1699 g participate in more sub-sets ofservers delivering decodable sets of fragments to assembling devicesthan servers 1699 a to 1699 c.

In one embodiment, the data center, such as 1671 and/or 1682, is anInternet service provider connected to the Internet via a fixedbandwidth link, which is used as a shared communication link to serverstransmitting general Internet traffic and fractional-storage serverstransmitting fragments. In one embodiment, the data center is acolocation center, having a limited link capacity to the Internet. Inone embodiment, the data center or the shared link is operated by anInternet bandwidth provider. In one embodiment, the data center isoperated by an ISP.

FIG. 11 illustrates one embodiment of alternative servers communicatingvia shared networks. Fractional-storage servers 1699 a′ to 1699 c′transmit erasure-coded fragment traffic over Internet backbone networksor Tier-1 networks 1661 and 1662. The fragment traffic and the generalInternet traffic transported via the networks are mixed together on thenetworks. Similarly, fractional-storage servers 1699 d′ to 1699 g′ areconnected to Internet backbone networks or Tier-1 networks 1663 and1664. In one embodiment, the fractional-storage servers are selected forfragment transmittal when the networks through which they transmitfragments to the Internet are loaded below a certain level. Thisprinciple is demonstrated by the following example: assuming that anythree fractional-storage servers out of 1699 a′ to 1699 g′ store adecodable set of fragments, the three servers will be selected accordingto the load of the network through which they communicate. If thegeneral Internet traffic transported via networks 1661, 1662 is close tothe maximal capacity of the networks, then using any of servers 1699 a′to 1699 c′ is not advisable. Instead, in a case where networks 1663,1664 are relatively unloaded with general Internet traffic, any threeservers out of servers 1699 d′ to 1699 g′ may be used. When thefractional-storage servers deliver fragments to many assembling devices,servers transmitting via relatively unloaded networks are preferred,such that the end effect is that servers 1699 d′ to 1699 g′ deliver ahigher fragment throughput than servers 1699 a′ to 1699 c′. In otherwords, servers 1699 d′ to 1699 g′ participate in more sub-sets ofservers delivering decodable sets of fragments to assembling devicesthan servers 1699 a′ to 1699 c′.

In one embodiment, the servers 1699 a′ to 1699 c′ and/or 1699 d′ to 1699g′ are connected to the backbone network or Tier-1 network via anInternet Exchange Point (“IX/IXP”). In one embodiment, the servers areconnected to the backbone network or Tier-1 network via a router of thenetwork or Tier-1 network, and are placed in a data center belonging tothe backbone network or Tier-1 network operator.

In one embodiment, the traffic loads on the shared links 1681 and 1682,or shared networks 1661, 1662 and 1663, 1664 change to below a firstlevel and above a second level, and the servers are dynamically selectedaccordingly. In one embodiment, the changes in the traffic loads resultfrom changes in local Internet traffic demands during a 24-hour cycle.Different servers are located in different time zones, such that thepeak of the changing traffic load occurs at different times fordifferent servers. Servers transmitting via relatively unloaded links ornetworks are preferred over servers transmitting via relatively loadedlinks or networks as the load cycle progresses. In one embodiment, theload changes below a first level and above a second level for differentlinks or networks at different times, and the servers are selectedaccordingly. For example, only servers that communicate via links ornetworks loaded below the first level are approached by the assemblingdevices.

In one embodiment, the load level metrics used to determinefractional-storage server selection preferences are approximatelyinversely proportional to the level of unutilized bandwidth left inshared links 1681 and 1682 or shared networks 1661,1662 and 1663, 1664,or any other shared links or networks of similar nature. The higher theunutilized bandwidth left in a link or network, the higher thepreference of using fractional-servers transmitting via that link ornetwork. In one embodiment, the level of unutilized bandwidth is madeavailable by the data center, and is represented in bits per second oras a percentage value out of the shared link's bandwidth capacity.

In one embodiment, the load level metrics used to determinefractional-storage server selection preferences are proportional to thelevel of general Internet traffic on shared links 1681 and 1682 orshared networks 1661,1662 and 1663, 1664. The lower the general traffictransported via a link or network, the higher the preference of usingfractional-servers transmitting via that link or network.

In one embodiment, the globally distributed assembling devices retrievefragments from the fractional-storage servers using a fragment pullprotocol, and determining which servers deliver fragments to whichassembling devices load balances the distributed system. In oneembodiment, the globally distributed assembling devices obtain fragmentsfrom fractional-storage servers using a push protocol with multiplesub-transmissions, and determining which servers deliver fragments viathe sub-transmissions to which assembling devices load balances thedistributed system.

In some embodiments, a push protocol is used to obtain fragments. A pushprotocol may be implemented using one transmission carrying fragmentsfrom a source server to a destination receiver, or may be implementedusing a plurality of sub-transmissions. When using sub-transmissions,each sub-transmission transports a fraction of the fragments needed forsegment reconstruction. Segments may be reconstructed from fragmentsreceived via sub-transmissions after obtaining decodable sets oferasure-coded fragments; optionally one set per segment. Asub-transmission may be transported using an IP stream such as RTP, anHTTPS session, or any other protocol suitable for transporting asequence of fragments between a source server and a destinationassembling device.

FIG. 12 illustrates one embodiment, in which content is segmented anderasure-coded. Fragments 390 a to 390(N), belonging to a first segment,are distributed to servers 399 a to 399(N) respectively. Other fragmentsbelonging to subsequent segments are similarly distributed to servers399 a to 399(N). The servers may use a push protocol to transport thefragments to an assembling device. A push protocol sub-transmission maycomprise a sequence of fragments associated with multiple segments. Inone example, the fragments are ordered according to the sequential orderof the segments in a streaming content. Server 399 a sends a firstsub-transmission to a destination assembling-device. Optionally, thefirst sub-transmission comprises a sequence of fragments starting withfragment 390 a, associated with the first segment, and continuing withfragments belonging to subsequent segments. Server 399 c sends a secondsub-transmission to the destination assembling-device, optionallystarting with fragment 390 c, associated with the first segment, andcontinuing with fragments belonging to subsequent segments. In a similarfashion, servers 399(N−1) and 399(N) send additional sub-transmissionsto the destination assembling-device, each comprising a unique fragmentsequence.

When using a push transmission, the assembling device does notexplicitly ask for each fragment, but instead instructs each of thedifferent servers to start sending it a fragment sequence using asub-transmission. The destination assembling-device receives thesub-transmissions sent by servers 399 a, 399 c, 399(N−1) and 399(N). Itgathers 573 the first fragment from each sub-transmission to reconstructthe first segment 101 a. In a similar fashion, additional fragmentsbelonging to subsequent segments are obtained from thesub-transmissions, and used to reconstruct the segments. It is notedthat any combination of sub-transmissions may be used, as long as adecodable set of fragments is obtained per each segment. It is alsonoted that FIG. 12 illustrates a non-limiting embodiment and asub-transmission may include two or more unique erasure-coded fragmentsper segment.

In one embodiment, the push sub-transmissions is synchronous (allservers sending the fragments of each segment at approximately the sametime). In another embodiment, the push sub-transmission is asynchronousand the arrival of different fragments associated with a specificsegment at the assembling device side may be spread over a long period.This may occur, as an example, when some push servers are faster thanothers. In one embodiment using asynchronous sub-transmissions, theassembling device aggregates whatever fragments it can beforepresentation time of each segment, and then optionally supplementsfragments using a pull retrieval process. A server that does not sendfragments fast enough, and therefore usually causes supplementalrequests, may be ordered to stop the sub-transmission. Another servermay be requested, optionally by the assembling device, to replace theslow server by initiating a new sub-transmission.

In one embodiment, the push-transmissions carry more erasure-codedfragments than needed for segment reconstruction. In one embodiment, thepush transmissions carry fewer erasure-coded fragments than needed forsegment reconstruction, and the remaining fragments are pulled by theassembling device.

In one embodiment, when the shared link or network is loaded below afirst level, the number of sub-sets in which the servers accessed viathe shared link or network are allowed to participate is increased inorder to increase the fragment consumption from these servers. When theshared link is loaded beyond a second level, the number of sub-sets isdecreased. In one example, the amount of fragment traffic transmitted bya server is directly coupled to the number of sub-sets in which theserver participates.

In one embodiment, the maximum number of sub-sets of servers deliveringdecodable fragments to assembling devices in which the servers accessedvia the shared links 1681 and 1682 or shared networks 1661,1662 and1663, 1664 are allowed to participate is approximately a decreasingfunction of the throughput of the general Internet traffic via theshared link or network. In one example, as the general trafficincreases, the server participates in fewer sub-sets, and above acertain point the server does not participate in any of the sub-sets.

In one embodiment, an assembling device will refrain from requestingfragments from a server encountering load conditions close to maximalload, or above a certain threshold. This mechanism may be used to lowerthe cost of placing a server or a virtual server in a colocation centeror any other data center, as the geographically distributedfractional-storage servers do not consume bandwidth and/or processingresources during peak load periods. Furthermore, this mechanism may beused to lower the cost of Internet bandwidth connections to thegeographically distributed fractional-storage servers, as the servers donot consume Internet bandwidth during peak load periods.

The term “erasure coding” as used herein denotes a process in which asequence of erasure-coded fragments can be generated from a segment suchthat the segment can be reconstructed from any or almost any subset ofthe erasure-coded fragments of size equal to or somewhat larger than thesize of the segment (sometimes may be referred to as “enougherasure-coded fragments” or “sufficient subset of fragments”). Examplesof erasure codes include, but are not limited to, rateless codes,Reed-Solomon codes, Tornado codes, Viterbi codes, Turbo codes, any Blockcodes, any Convolutional codes, and any other codes that are usuallyused for forward error correction (FEC).

The term “rateless coding” as used herein denotes a type of erasurecoding in which a very long, potentially limitless, sequence ofrateless-coded fragments can be generated from a segment such that thesegment can be reconstructed from any or almost any subset of therateless-coded fragments of size equal to or somewhat larger than thesize of the segment (sometimes may be referred to as “enoughrateless-coded fragments”). Examples of rateless codes include, but arenot limited to, Raptor codes, LT codes, online codes, any Fountaincodes, and any other Rateless codes.

The term “erasure-coded fragment” denotes a fragment comprising dataencoded with an erasure code (which may also be a rateless code in someembodiments). The term “rateless-coded fragment” denotes a fragmentcomprising data encoded with a rateless code.

The term “assembling device” as used herein denotes a computing devicethat retrieves erasure-coded fragments from servers over a network. Theassembling device may perform one or more of the following: (i) Decodethe retrieved erasure-coded fragments into segments. (ii) Present thecontent reconstructed from the retrieved erasure-coded fragments. (iii)Act as a bandwidth amplification device, by receiving, storing, andforwarding erasure-coded fragments. In some embodiments, the assemblingdevice may be any device located at the user premises, like an STB, PC,gaming console, DVD player, PVR device, or any other device able toretrieve erasure-coded fragments from a communication network. In someembodiments, the assembling device may be an assembling server. In someembodiments, the assembling device may be any computational device withaccess to a communication network, located at a central office, datacenter, BRAS location, ISP premises, or any other place with directnetwork connectivity. In one embodiment, the assembling device iscoupled to a display device used for content presentation.

The abbreviation CDN denotes “Content Delivery Network”. The term “CDNserver” as used herein denotes a server having one or more of thefollowing characteristics: (i) A bandwidth (CDN_BW) that is much greaterthan the average bandwidth consumed by a user premises device (User_BW)receiving video streaming content. In some examples, the CDN_BW is atleast 10 times, 100 times, 1,000 times, or 10,000 times greater than theUser_BW. (ii) The server is located outside the last mile communicationinfrastructure of the end users, such that the CDN server and the endusers are located in different networks. For example, the CDN server isnot located under a BRAS, while the end users are located under a BRAS.Moreover, in some embodiments, the CDN servers are deployed over a widearea across the Internet and optionally located close to or on theInternet backbone. In some embodiments, the CDN server does not usuallyretrieve and play streaming content. In some embodiments, the CDN serverhas a much greater storage space than the storage space of an averageplayer of streaming content.

The term “fractional-storage server” in the context of erasure-codedfragments (also applicable to “fractional-storage CDN server”), as usedherein denotes a server that (i) stores less than the minimum quantityof erasure-coded fragments required to decode the erasure-codedfragments, and (ii) where at least a meaningful quantity of the storederasure-coded fragments is not stored in order to be consumed by thefractional-storage server.

The term “streaming content” as used herein denotes any type of contentthat can begin playing as it is being delivered. Streaming content maybe delivered using a streaming protocol, a progressive downloadprotocol, or any other protocol enabling a client to begin playing thecontent as it is being delivered. Moreover, the term “streamingprotocol” includes “progressive download protocol”. In addition, theverb “streaming” refers to using a streaming protocol, using aprogressive download protocol, or using any other protocol enabling thereceiver to begin playing the content as it is being delivered.

In some embodiments, expressions like “approximately sequentialsegments” may denote one or more of the following non-limiting options:segments that are sequential (in time or according to a file's order),segments that are approximately sequential (such as segments with someinterlace, or segments without a great amount of non-sequential data),segments generated sequentially and/or approximately sequentially fromdifferent components of content (such as storing the i-frames andp-frames of a compressed content in different segments), and/or othersequential or approximately sequential segmentation after classificationor separation into different components and/or elements.

FIG. 12 illustrates one embodiment of a server array includingfractional-storage servers 399 a to 399(N) storing erasure-codedfragments 390 a to 390(N) associated with content. In order forassembling device 661 to reconstruct a segment 101 a of the content, ithas to retrieve at least K erasure-coded fragments. In one example, k=4and the assembling device 661 chooses approximately randomly from whichservers to retrieve the 4 different erasure-coded fragments. It choosesto retrieve fragments 390 a, 390 c, 390(N−1) and 390(N), which are notedas group 573, and reconstruct the segment 101 a. Consequent segments ofthe content are reconstructed in a similar fashion, and the content mayeventually be fully retrieved by combining all relevant segments. If theassembling device 661 cannot reconstruct the segment 101 a, it retrievesone or more additional unique erasure-coded fragments, and tries again.

In one embodiment, the content being distributed supports streampresentation, and segment 101 a is of small size, to enable contentpresentation by assembling device 661 shortly after beginning thereception of the segment (or any other segment of the content). Forexample, segment 101 a is 96 KByte, allowing a 5 Mbps download speedreceiver to obtain the entire segment (by requesting enougherasure-coded fragments to enable the reconstruction of the segment, andsuch that the total size received of all requested erasure-codedfragments is slightly larger than the segment) after approximately 0.2seconds from request, and beginning the presentation shortly or rightafter the successful decoding and reconstruction of segment 101 a.

The term “approximately random” as used herein refers to, but is notlimited to, random, pseudo random, and/or based on a long list ofnumbers featuring very low autocorrelation and very low correlation withother similar lists of numbers.

In some embodiments, the fragments are small enough to be contained inone packet. In one embodiment, each fragment is about 1400 bytes, andcan fit into one UDP or RTP packet transmitted over Ethernet. Thestateless nature of UDP and RTP allows the servers to send one packetwith one fragment very quickly, without the need for any acknowledgementor hand shaking. In some embodiments, the fragment pull protocolrequests use one stateless packet, like UDP or RTP. In one embodiment,the assembling device requests about 100 fragments approximately inparallel, using 100 separate requests or one or few aggregated requests.About 100 servers respond by sending about 100 fragments, eachencapsulated in one stateless packet, after a short delay, and theassembling device receives the fragments within a fraction of a second.Assuming an Internet round trip delay of 100 ms, and server processinglatency of 100 ms, then after 200 ms the assembling device startsreceiving all 100 fragments. With a modem of 5 Mbps, and assuming 1400bytes per fragment, all 100 fragments are received 1400×100×8/5 Mbps=224ms after the initial delay, meaning that content can be presented200+224=424 ms after request (decoding and other process time has beenignored in this example).

FIG. 13 illustrates in one embodiment wherein server 369 a operates as astand-alone content distributor. Server 369 a stores all theerasure-coded fragments 311 a to 311(N) of the content. Assemblingdevice 661 assembles the content from server 369 a, by requesting therelevant erasure-coded fragments. The request may be per specificerasure-coded fragment, or per a cluster of erasure-coded fragments.Upon each request, server 369 a sends the one or more requestederasure-coded fragments. The erasure-coded fragments 311 a to 311(N) maybe encoded using erasure codes, or, alternatively, not encoded at alland simply constituting a fragmented sequence of the content. Theoptional groups of bandwidth amplification devices 611 a, and 611 b to611N store fragments 311 a, and 311 b to 611(N) correspondingly (andother fragments). In one embodiment, assembling device 661 can requestfragments from a group of bandwidth amplification devices instead of theserver 369 a. In one embodiment, the bandwidth amplification devices arefractional-storage assembling devices that receive their fragments froma single server 369 a containing all the fragments, or from a group ofservers or a control entity that contain some or all of the fragments.Upon adding another server 369 b, which stores the same erasure-codedfragments as server 369 a, assembling device 661 may retrieve thefragments from server 369 a, and/or from server 369 b, and/or from theoptional bandwidth amplification devices 611 a to 611N. For assemblingdevice 661, switching between servers is seamless when using a fragmentpull protocol because it simply means requesting the next fragments froma different source.

The following embodiments describe processes for on-the-flyerasure-coded fragment retrieval from fractional-storage servers.

In one embodiment, a method for obtaining erasure-coded fragments fromfractional-storage servers to reconstruct a segment includes thefollowing steps: (i) identifying the next segment to be obtained;optionally, the segments are approximately sequential segments ofstreaming content obtained according to their sequential order; (ii)optionally, determining the minimum number of fragments needed toreconstruct the segment; (iii) are enough identified relevant servers(i.e. servers storing the required fragments) available from the processof obtaining prior segment/s? (iv) if no, identifying enough relevantservers; (v) if yes, requesting enough fragments from the identifiedrelevant servers; if less than enough fragments are obtained from theidentified relevant servers, go back to step iv and identify additionalrelevant server/s; (vi) reconstruct the segment from the obtainedfragments; and (vii) optionally, go back to step i to obtain the nextsegment.

In one embodiment, a method for obtaining erasure-coded fragments fromfractional-storage servers to reconstruct multiple segments includes thefollowing steps: (i) identifying multiple segments to be obtained,optionally according to their sequential order; (ii) optionally,determining the minimum number of fragments needed to reconstruct thesegment; (iii) optionally, determining the number of fragments to beobtained approximately in parallel; (iv) are enough identified relevantservers available from the process of obtaining prior segment/s? (v) ifno, identifying enough relevant servers; (vi) if yes, requesting enoughfragments from the identified relevant servers, optionally in paralleland according to the sequential order of the segments; (vii) if lessthan enough fragments are obtained from the identified relevant servers,go back to step iv and identify additional relevant server/s; (viii)reconstructing the segment/s from the obtained fragments; and (ix)optionally, go back to step i to obtain the next segments.

In one embodiment, a method for obtaining erasure-coded fragments fromfractional-storage servers to reconstruct a segment in a burst modeincludes the following steps: (i) identifying the next segment to beobtained; (ii) optionally, determining the minimum number of fragmentsneeded to reconstruct the segment; (iii) are more than the minimumnumber of relevant servers available from the process of obtaining priorsegment/s? (iv) if no, identifying more than the minimum relevantservers; (v) if yes, requesting more than the minimum number offragments needed to reconstruct the segment; if less than enoughfragments are obtained, go back to step iv and identify additionalrelevant server/s; (vi) reconstructing the segment from the obtainedfragments; and (vii) optionally, go back to step i to obtain the nextsegment.

The various methods for obtaining erasure-coded fragments from thefractional-storage servers for reconstructing one or more segments maybe combined as needed. In one example, the initial segment/s areobtained using a burst mode and the following segments are retrievedwithout requesting extra fragments. In another example, the initialsegment/s are obtained approximately in parallel and optionally using aburst mode, and the following segments are obtained one by one andoptionally without requesting extra fragments. The fragments may beobtained using a pull protocol and/or a push protocol. Moreover, theservers from which to retrieve the fragments may be selected accordingto one or more of the various discussed methods for selecting theservers and/or load balancing the servers.

FIG. 14 illustrates one embodiment of real time streaming contentretrieval from fractional-storage servers. An assembling device begins aprocess of obtaining streaming content 700 for presentation. Starting atT1, the assembling device requests erasure-coded fragments 720 a to720(K). By T2, all K erasure-coded fragments are obtained, and at timeT2 b until T4, erasure-coded fragments 720 a to 720(K) are decoded intosegment 710 a. The retrieval time of the erasure-coded fragments and thesegment decoding time should be equal to or faster than thecorresponding presentation time, in order to enable a continuouspresentation, once presentation begins at T5. T2 b minus T2 is a shortdelay, and can be fractions of a second. Subsequent erasure-codedfragments 730 a to 730(K) are retrieved between T2 and T3, and aredecoded into subsequent segment 710 b between T4 and T6.

In one example, the streaming content 700 is encoded at 1 Mbps, and thesegment size is 96 Kbytes. The presentation of each segment takes about0.77 seconds. Retrieving fragments 720 a to 720(K) takes no more than0.77 seconds, meaning that the assembling device's connection bandwidthmust be 1 Mbps or higher. Decoding segment 710 a takes no more than 0.77seconds. If a small delay of 0.2 seconds is assumed for both T2 b minusT2 and T5 minus T4, then T5 can start at 0.77+0.2+0.77+0.2=1.94 secondsafter T1, meaning that presentation can begin about 2 seconds followingrequest of the first erasure-coded fragment. In another example, theretrieval process and the decoding process are performed faster than thereal time presentation bounds, therefore enabling a shorter time to playand a download rate that exceeds the presentation rate.

In one embodiment, the erasure-coded fragments 720 a to 720(K) areretrieved in approximately random order, or any other order, as long asat least the K erasure-coded fragments needed for decoding the segment710 a are available until time T2.

FIG. 15 illustrates one embodiment where the erasure-coded fragments 720a to 720(K) are retrieved in approximately random order 720(K−1), 720 a,720(K), 720 b, or any other order, as long as at least the Kerasure-coded fragments needed for decoding the segment 710 a areavailable until time T2. Similar retrieval in random order is applied toerasure-coded fragments 730 a to 730(K) and all other subsequentfragments.

In one embodiment, the fragments associated with sequential segments ofstreaming content are delivered to an assembling device as a pluralityof sub-transmissions. In this case, each fractional-storage serverparticipating in the delivery of the fragments to the assembling devicesends a transmission to the assembling device comprising a sequence oferasure-coded fragments. This transmission is referred to as asub-transmission. In one example, each sub-transmission contains atleast one fragment per each sequential segment of the streaming content.In one example, the sub-transmission starts at a segment indicated bythe assembling device, and continues from that point onwards,approximately according to the sequential order of segments, until theassembling device instructs the server to stop, or until reaching thelast segment of the content. Each sub-transmission carries only afraction of the fragments (per segment) needed to reconstruct thesegments of the streaming content, such that the combination of at leasttwo sub-transmissions received by the assembling device from the serversallows the assembling device to obtain enough fragments needed toreconstruct each segment.

In one embodiment, each sub-transmission is delivered to the assemblingdevice via a streaming session, such as an RTP session, wherein the RTPpackets transport the fragment sequence approximately according to theorder of the sequential segments. In one embodiment, eachsub-transmission is delivered to the assembling device via an HTTPconnection, or other closed-loop data transfer mechanisms over TCP/IP.In one embodiment, the assembling device may change one or moretransmitting servers on the fly, by instructing the server(s) to stopsending an already active sub-transmission—as may be needed in a case ofan RTP session, and initiating new sub-transmissions from other serversinstead. Replacement of transmitting servers on the fly may be needed ina case of a server failure, network failure, or high load or latencyconditions.

FIG. 16 illustrates one example of a fractional-storage systemcomprising servers 699 a to 699(N) having a bandwidth capability 681. Inother words, no server can send data at a rate higher than 681.Assembling device 661 can select from which servers to obtainerasure-coded fragments for reconstruction of a segment. In one example,each server stores one relevant, unique, erasure-coded fragment.Therefore, from the N servers storing N possible unique fragments, theassembling device needs only K erasure-coded fragments for completereconstruction of the segment (K<N). Since it is not important which Kfragments from the N are retrieved, the assembling device may retrievefrom the least loaded servers, so as to keep the load between thedifferent servers balanced. When many assembling devices assemblecontents in parallel, and since all assembling devices can select theleast loaded servers, the end effect is that the load on the servers isbalanced, with the potential for most servers to approach their maximalbandwidth capabilities. Optionally, that load balancing is achievedwithout significant coordination between the servers.

In the example of FIG. 16, assuming that K=3, the assembling device 661may select servers 699 b, 699(N−1), and 699 a for fragment retrieval, asthey have the lowest load of all N servers. Servers 699 c and 699(N), asan example, will not be chosen, as they have relatively higher loads.

The assembling device may select the least loaded servers using anyappropriate method, such as, but not limited to (i) accessing a centralcontrol server having data about the load conditions on the variousservers, or (ii) periodically querying the various servers on their loadconditions.

In one embodiment, instead of, or in addition to, selecting the leastloaded servers, the assembling device 661 tries a random set of Kservers from the N, and retrieves erasure-coded fragments from allservers reporting a load below a threshold, while higher loaded serverswill be replaced by least loaded servers from the possible N servers.The end result is that the server array is balanced because the Kerasure-coded fragments are retrieved from servers loaded below thethreshold.

In one embodiment, the assembling device does not know which of theservers store erasure-coded fragments related to the content to beretrieved, but the assembling device knows over how many servers (fromthe total number) the erasure-coded fragments are distributed.Therefore, the assembling device compensates for the infertile requestsby enlarging the number of requests for erasure-coded fragments.Optionally, the requested servers are selected based on approximatelyrandom algorithm.

FIG. 17 illustrates one embodiment of different servers 698 a to 698(N)having different bandwidth capabilities of 683 a to 683(N)correspondingly. Assembling device 661 selects from which K servers, outof the possible N, to retrieve the fragments for segment reconstruction,wherein each server may have different unutilized bandwidth anddifferent bandwidth capability. When many assembling devices assemblecontents in parallel, while rejecting servers with a high load, the endeffect is that the server array is approximately balanced and mostservers can approach their maximal bandwidth capabilities. In oneembodiment, the server array is balanced by enabling many assemblingdevices to select the least loaded servers. In the example, and assumingthat K=3, servers 698 a, 698(N−1) and 698(N) will be selected, as theyhave the highest unutilized bandwidth. In another example, the servershaving the highest percentage of unutilized bandwidth will be selected.

In one embodiment, servers 698 a to 698(N) represent completelydifferent types of server hardware, operating systems and capabilities,all put together in an array, and achieving load balance without theneed for significant inter-server coordination. In one example, thefragments are distributed to at least two different classes of servers;the first class comprises high bandwidth CDN servers directly connectedto the Internet backbone, and the second class comprises lower bandwidthCDN servers not directly connected to the Internet backbone.

In one embodiment, the servers are selected for fragment retrievalaccording to their unutilized fragment delivery bandwidth. For example,the servers report their unutilized bandwidth, and the assemblingdevices, or a control server, obtain the report and decide which serversto use for fragment delivery based on the unutilized bandwidth of eachserver.

In one embodiment, the servers are selected for fragment retrievalaccording to their ability to support additional fragment delivery load.For example, the servers report their ability to support additionalfragment delivery loads. And the assembling devices, or a controlserver, obtain the report, and select the servers that report an abilityto support additional fragment delivery loads.

In one embodiment, the assembling device, or a control server, looks fora pool of servers that may be used as replacements for servers that areloaded to a degree that does not allow continuation of fragmentdelivery. For example, the assembling device looks for potentialunloaded servers, while retrieving fragments from other servers. Theassembling device may sample relevant servers approximately randomly,and/or according to indications from a control server. The samplingprocess may comprise querying the potential server for load information,or measuring the latency or latency variance to the servers in order toestimate the current load on the server.

In one embodiment, it is desired to replace one or more servers by otherservers for the delivery of erasure-coded fragments, wherein thereplacement servers are selected using a second criterion from a pool ofservers identified using a first criterion. For example, the firstcriterion for identifying the pool of replacement servers compriseslooking for servers capable of increasing their fragment deliverythroughputs, and the second criterion for selecting the replacementservers from the pool comprises selecting the best latency responseserver from the pool. In one example, the first criterion is a latencycriterion, and the second criterion is a load criterion. In anotherexample, the first criterion is a latency criterion, and the secondcriterion is a latency variance criterion. In another example, thesecond criterion is an approximately random selection. In oneembodiment, a server selected using the second criterion is compared tothe server to be replaced based on the second criterion. For example,the second criterion is latency, and the replacing server, selected fromthe pool, has a smaller latency than the server it replaces.

In one embodiment, the server to be replaced is identified by comparingthe actual performance level of the server with a threshold performancelevel. For example, when the compared performance is latency, a serverhaving response latency above a certain threshold is replaced. Inanother example, the compared performance is the load on the server,which may be measured in terms of the amount of the unutilized fragmentdelivery bandwidth, or in terms of the percent of the server'sunutilized fragment delivery bandwidth, or measured by any otherappropriate technique.

In some embodiments, the assembling devices use a fragment pull protocolto retrieve the fragments and approach the servicing servers. In someembodiments, the assembling devices use a push protocol to obtain thefragments and approach the servicing servers, possibly by obtainingmultiple sub-transmissions comprising fragment sequences.

FIG. 18 illustrates one embodiment of a fractional-storage system.Assembling device group 661 g obtain erasure-coded fragments from theservers, such that the resulting outgoing bandwidth utilizations of eachserver in the array is 682 a to 682(N) correspondingly. FIG. 19illustrates a case where server 698 b has failed, its bandwidthcapability 682 b 1 is zero, and is therefore unable to provideerasure-coded fragments. The assembling devices from group 661 g, whichpreviously obtained fragments from server 698 b, may attempt to accessit again for additional fragments, but are now unable to get a response.These assembling devices therefore obtain fragments from alternativeservers. The end effect is that bandwidth 682 b is now loaded on thestill available servers, such that the total bandwidth 682 a 1 to682(N)1 approximately increases by a total amount equal to 682 b,optionally with no inter-server coordination, and simply by the factthat each assembling device selects alternative available servers forobtaining fragment on-the-fly. In one example, instead of obtaining fromserver 682 b 1, the assembling devices obtain from the least loadedavailable servers. In one embodiment, a control server selects thealternative server/s for the assembling devices. In one embodiment, theassembling devices use a fragment pull protocol to obtain the fragments,and approach the alternative servers. In one embodiment, the assemblingdevices use a push protocol to obtain the fragments, and approachalternative servers, possibly by obtaining multiple sub-transmissionscomprising fragment sequences. In this case, the sub-transmissions ofthe faulty server are discontinued and compensated for by othersub-transmissions from the alternative servers.

FIG. 20 illustrates an example similar to FIG. 19 with the differencethat servers 698 a, 698 b, and 698 c to 698(N) reside within, or getserviced via, first, second, and third Internet backbone providers 300j, 300 i, and 300 h correspondingly. The group of assembling devices 661g is connected to the Internet via network 300 k, which has access toall three backbones, such that communication between the assemblingdevices and servers 698 a to 698(N) pass via at least one of thebackbones, or more. If server 698 b is made unavailable to theassembling devices, optionally not due to a server failure, but ratherdue to congestion or a failure of the second Internet backbone provider300 i, assembling devices 661 g compensate for the lost bandwidth byswitching to the available servers on-the-fly. In one embodiment,networks 300 h, 300 i, and 300 j, are different physical sub-nets of onenetwork connected to the Internet. In one embodiment, the assemblingdevices are connected to networks 300 h, 300 i, and 300 j, via network300 k, and then via one or more Internet Exchange Points (“IX/IXP”).

Referring again to FIG. 19, in one embodiment server 698 b fails and areplacement is needed. The replacing server (not illustrated) may storeeither the same erasure-coded fragments stored on server 698 b, or storeother unique erasure-coded fragments associated with the segments storedon 698 b. One method for regenerating the erasure-coded fragments storedon server 698 b, or generating equivalent unique erasure-codedfragments, includes the following steps: (i) identifying afailed/non-responsive server. (ii) determining the segmentscorresponding to the erasure-coded fragments that were stored on thenon-responsive server. This may be achieved either by a query to acontrol server, or by a query to servers in the distributed storage thatservice the same contents. (iii) reconstructing each segment whoseerasure-coded fragments are to be regenerated. This may be achieved byretrieving and decoding enough erasure-coded fragments. (iv) re-encodingat least the required erasure-coded fragments from the reconstructedsegments. The re-encoded fragments may be the same as the erasure-codedfragments previously stored on non-responsive server 698 b, or may benew, unique erasure-coded fragments. And (v) distributing the requirederasure-coded fragments to a new replacement server for 698 b.

FIG. 21 illustrates a few examples of retrieving fragments according tolocality. In one example, the fractional-storage servers are connectedto a data network or networks comprising the routers 201 to 209.Assembling devices 235, 237, and 238 are connected to the same datanetwork or networks, and K=3, meaning that any assembling device needsto obtain 3 erasure-coded fragments per segment from optionally 3different servers out of the 10 in order to successfully reconstruct thesegment.

Each assembling device tries to obtain erasure-coded fragments fromfractional-storage servers that are closest to it topologically. In oneembodiment, the topological distance is a function of the number ofseparating routers. Assembling device 238 can select three servers fromgroups 242, 248 or 249. According to the minimal path criterion, itretrieves the erasure-coded fragments from servers 399 h to 399 i ofgroup 248, since they are only one router 208 away. Groups 242 and 249are three (208, 202, 203) and five (208, 202, 203, 201, 209) routersaway, and are therefore not selected for retrieval. Similarly, device237 selects three servers out of group 242, and device 235 can selectany three servers from groups 242 and 249, since both are located fourrouters away.

In one embodiment, if topologically close servers do not respond to theassembling device, or report a bandwidth limitation, the assemblingdevice will attempt to obtain an erasure-coded fragment from the nexttopologically closest server.

In one embodiment, an assembling device attempts to obtain erasure-codedfragments from servers featuring the lowest latency. Upon no response,for whatever reason, the assembling device will attempt to retrieve fromthe next lowest latency server. In one embodiment, the assembling deviceobtains information regarding the unutilized fragment deliverybandwidths of servers, and then attempts to retrieve from the lowestlatency servers out of the servers having enough unutilized bandwidth.In one embodiment, the assembling device obtains information regardingthe unutilized fragment delivery bandwidths of the servers, and thenattempts to retrieve from the topologically closest servers out of theservers having enough unutilized bandwidth.

Still referring to FIG. 21, in one embodiment the assembling devicesselect servers according to a latency criterion, such as selectingservers with the shortest time between fragment request and fragmentdelivery, or selecting servers having latency below a dynamic or staticthreshold. Assembling device 237 assembles content from servers 399 c,399 f, 399 g, and assembling device 235 assembles content from servers399 b, 399 c, 399 g (both use a mixture of servers from groups 242 and249). At a certain point in time, router 209 becomes congested orblocked, and prevents the erasure-coded fragments from servers 399 b and399 c from arriving at assembling devices 235 and 237, or causes thefragments to arrive with an increased delay. Therefore, assemblingdevice 235 switches to three servers of group 242, and assembling device237 switches from server 399 c to server 399 e.

In one embodiment, the assembling device selects fractional-storageservers according to the following criterion: first, servers withadequate unutilized fragment delivery bandwidth are considered, then outof these, those with latency below a threshold are considered, and outof these, the servers with minimal topological routing path areselected.

In some embodiments, the assembling devices use a fragment pull protocolto retrieve the fragments, and approach servers having low latency orlow hop count as compared to other servers. In some embodiments, theassembling devices use a push protocol to retrieve the fragments, andapproach servers having low latency or low hop count as compared toother servers, optionally by obtaining multiple sub-transmissionscomprising fragment sequences.

In one embodiment, a plurality of unsynchronized retrieving assemblingdevices, which optionally use fragment pull protocol, choose the leastloaded servers from which to retrieve the erasure-coded fragments.Optionally, the servers have almost no inter-communication between themand the load balancing calculation is performed by the retrievingassembling devices. Because the assembling devices can select the leastloaded servers, the assembling devices manage the load balancing. Whenthe erasure-coded fragments stored by the servers are uniqueerasure-coded fragments, the retrieving assembling device may retrieveerasure-coded fragments from any relevant server. Therefore, it may beenough for the retrieving assembling device to have indication of theload on its targeted servers, and retrieve enough erasure-codedfragments from the least loaded servers.

In one embodiment, a server signals the retrieving assembling devicethat it is close to its bandwidth limit and the assembling devicesearches for an alternative server. Optionally, the assembling deviceselects the server according to one or more of the following parameters:locality, cost, latency, or reliability. In one embodiment, the serversregister their loads on a central server, and the assembling deviceselects the server to retrieve from, from the registered servers. In oneembodiment, a central server, holding the loads of the various servers,determines for the assembling devices from which server to retrieve theerasure-coded fragments.

In one embodiment, assembling devices measure the latency of thedifferent servers in responding to fragment requests, and then use thelatency information to estimate the loads on the servers. In oneexample, a high latency may indicate a high load on the server.

In one embodiment, the topological router hop count between anassembling device and fragment delivering servers is used to estimatethe latency of the servers in responding to fragment requests.

In one embodiment, the latency of fragment delivering servers inresponding to fragment requests by an assembling device is used toestimate the topological router hop count between an assembling deviceand the servers.

In one embodiment, the assembling devices perform several latencymeasurements for the different servers in responding to fragmentrequests, and then use the latency variance information to estimate theloads on the servers. In one example, a high latency variance maysuggest a high load on server.

In one embodiment, fractional-storage servers, from which the fragmentsare obtained for reconstructing a segment, are selected based on anapproximately random selection algorithm from all of the servers storingthe relevant fragments. In one example, an approximately randomselection algorithm weighted according to the unutilized bandwidth ofthe servers is used for the approximately random selection of servers.The weighted random selection algorithm assigns servers with selectionprobabilities proportional to the amount of unutilized bandwidth forfragment delivery in each of the servers, such that the probability toselect a server having a larger amount of unutilized bandwidth is higherthan the probability to select a server having a lower amount ofunutilized bandwidth.

The following embodiments describe processes for on-the-fly selectionand re-selection of fractional-storage servers from which to obtainerasure-coded fragments.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on the unutilized bandwidth of the servers,includes the following steps: (i) accessing data regarding serversstoring relevant fragments (referred to as the relevant servers); (ii)accessing data regarding the unutilized bandwidth of the relevantservers. Optionally, the data is received by the assembling device fromthe relevant servers; and (iii) obtaining fragments from enough of therelevant servers having approximately the highest unutilized bandwidth;or obtaining fragments from enough of the relevant servers selectedrandomly and having unutilized bandwidth above a certain threshold.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on latency, includes the following steps: (i)accessing data regarding the relevant servers; (ii) accessing dataregarding the latencies from the relevant servers to the assemblingdevice; and (iii) obtaining fragments from enough of the relevantservers having the lowest latencies; or obtaining fragments from enoughof the relevant servers selected randomly and having latencies below acertain threshold.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on bandwidth and latency, includes thefollowing steps: (i) accessing data regarding the relevant servers; (ii)accessing data regarding the unutilized bandwidth of the relevantservers; (iii) identifying more than enough relevant servers having themost unutilized bandwidth; or randomly identifying more than enoughrelevant servers having unutilized bandwidth above a certain threshold;(iv) accessing data regarding the latencies from the identified serversto the assembling device; and (v) obtaining fragments from enough of theidentified servers having the lowest latencies; or obtaining fragmentsfrom enough of the relevant servers selected randomly and havinglatencies below a certain threshold.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on latency and bandwidth, includes thefollowing steps: (i) accessing data regarding the relevant servers; (ii)identifying more than enough relevant servers having latencies to theassembling device below a certain threshold; or randomly identifyingmore than enough relevant servers having latencies to the assemblingdevice below a certain threshold; (iii) accessing data regarding theunutilized bandwidth of the identified servers; and (iv) obtainingfragments from enough of the identified servers having the highestunutilized bandwidth; or obtaining fragments from enough of the relevantservers selected randomly and having the highest unutilized bandwidth.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on locality, includes the following steps:(i) accessing data regarding the relevant servers; (ii) accessing dataregarding the network topology distance (locality) from the relevantservers to the assembling device; and (iii) obtaining fragments fromenough of the topologically closest relevant servers; or obtainingfragments from enough of the relevant servers that are located in thesame sub-network as the assembling device, or located in the closestsub-networks.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on bandwidth and locality, includes thefollowing steps: (i) accessing data regarding the relevant servers; (ii)accessing data regarding the unutilized bandwidth of the relevantservers; (iii) identifying more than enough relevant servers having themost unutilized bandwidth; or randomly identifying more than enoughrelevant servers having unutilized bandwidth above a certain threshold;(iv) accessing data regarding the network topology distance from therelevant servers to the assembling device; and (v) obtaining fragmentsfrom enough of the topologically closest relevant servers; or obtainingfragments from enough of the relevant servers that are located in thesame sub-network as the assembling device, or located in the closestsub-networks.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on latency and locality, includes thefollowing steps: (i) accessing data regarding the relevant servers; (ii)identifying more than enough relevant servers having latencies to theassembling device below a certain threshold; or randomly identifyingmore than enough relevant servers having latencies to the assemblingdevice below a certain threshold; (iii) accessing data regarding thenetwork topology distance from the relevant servers to the assemblingdevice; and (iv) obtaining fragments from enough of the topologicallyclosest relevant servers; or obtaining fragments from enough of therelevant servers that are located in the same sub-network as theassembling device, or located in the closest sub-networks.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments is based on bandwidth, latency, locality, and,optionally, one or more additional relevant parameters. The method mayweigh the different parameters in various ways, all of them are intendedto be covered by the embodiments. For example, the method may includethe following steps: (i) accessing data regarding the relevant servers;(ii) receiving data regarding the unutilized bandwidth latencies to theassembling device, and topology distances to the assembling device;(iii) weighting the received data and identifying a quantity of the mostproper relevant servers, which can provide enough fragments toreconstruct content; and (iv) obtaining the fragments from theidentified servers. In another example, the method may include thefollowing steps: (i) accessing data regarding the relevant servers; (ii)identifying a set of more than enough relevant servers having the mostunutilized bandwidth; or randomly identifying a set of more than enoughrelevant servers having unutilized bandwidth above a certain threshold;(iii) from the set, identifying a sub-set of more than enough relevantservers having latencies to the assembling device below a certainthreshold; or randomly identifying more than enough relevant servershaving latencies to the assembling device below a certain threshold; and(iv) obtaining fragments from enough of the topologically closestrelevant servers out of the sub-set; or obtaining fragments from enoughof the relevant servers out of the sub-sets, which are located in thesame sub-network as the assembling device, or located in the closestsub-networks.

In one embodiment, a server may be loaded to a point that it isapproximately unable to transmit additional fragments as a response tonew fragment requests or new sub-transmission requests. The server mayalso be too loaded to continue transmitting fragments to its currentlyserved assembling devices. In one example, these cases result from oneor more of the following conditions: (i) server hardware limitation,such as CPU power or memory bus constraints, which prevents it fromdelivering fragments beyond a certain throughput, (ii) outgoingcommunication link limitation, such as a fixed-bandwidth line, whichprevents the server from transmitting fragments beyond a rate that canbe supported by the line, (iii) sharing of an outgoing communicationline with other servers, and the other servers utilizing the shared lineto a point that lowers the bandwidth available for fragmenttransmission, and (iv) sharing the fragment storage and transmissionsoftware together with other applications on one physical server, andthe other applications consuming CPU, memory, or communication resourcesto a point that affects the ability of the fragment storage andtransmission software to respond to fragment or sub-transmissionrequests.

In some embodiments, approximately random selection offractional-storage servers is utilized for dealing with changes innetwork conditions, such as packets loss and/or server failure, withoutaffecting the user experience, and optionally without prior knowledge ofthe type of the change in network condition. Optionally, newerasure-coded fragments are requested from the randomly selected serversinstead of failed requests. Optionally, failed servers are replaced withother servers. Optionally, the combination and/or the number offractional-storage servers from which the fragments are obtained changesover time. Optionally, the number of redundant fragment requests changesover time.

In one example, a constant packet loss condition causes a constantfragment loss condition, which means that a certain percentage offragments fail to be obtained by the assembling device. In this case, anapproximately random selection of new servers may solve the problem, notnecessarily because of the randomness of the selection (a generalfragment loss condition may affect all servers), but simply because itgenerates more fragment requests to compensate for the loss, resultingin an increased fragment-delivery throughput that approximately levelsat an average steady state value of:(Nominal_Throughput/(1−Fragment_Loss Ratio)), wherein theNominal_Throughput is the fragment-delivery throughput resulting when nopackets are lost, and the Fragment_Loss_Ratio is the(fragment_lost/fragments_sent) ratio, which is a parameter thatincreases monotonically with the packet-loss. In another example, thefailure is specific to one or more servers, and the approximately randomselection of new servers finds new servers having lower failure ratios.In this case, the random selection solves the problem, since trying toretrieve again from problematic servers may have no positive effect. Theabove two examples demonstrate how a single selection strategysuccessfully copes with different types of failures, while resulting ina different behavior according to the type of failure (differentresulting fragment delivery rates for example), and all that withoutprior knowledge of the exact nature of the failure. In another example,the servers are deployed over multiple networks and the communicationfault comprises a failure of one of the networks causing related serversto be inaccessible. As a solution, the assembling device approximatelyrandomly reselects the servers until it communicates with enoughaccessible servers to reconstruct a segment. Other examples arepossible, in which an unknown failure is correctly handled byapproximately random on-the-fly server selection.

In one embodiment, different servers receive different weightsproportional to their bandwidth. For example, the higher the bandwidthcapability of the server, the higher the server coefficient; the higherthe server coefficient, the higher the probability of selecting theserver by an assembling device. In one embodiment, selecting the serversapproximately randomly enables the fractional-storage system to operatewell when the assembling devices do not know the load on at least someof the servers.

In one embodiment, the approximately random selection of serversproduces a set of source servers from which erasure-coded fragments areretrieved using a fragment pull protocol. In another embodiment, theapproximately random selection of servers produces a set of sourceservers from which erasure-coded fragments are retrieved using apush-protocol. In this case, multiple sub-transmissions may be used totransport the fragments from multiple servers to an assembling device.When new server sources are randomly selected instead of others, theassembling device may end the sub-transmissions associated with thereplaced servers, and initiate new sub-transmissions from the replacingservers, optionally from the point that the terminated sub-transmissionswere interrupted.

In one embodiment, the approximately random server selections are madefrom the servers not currently servicing the assembling device. In oneembodiment, the approximately random server selections are made from allservers storing relevant fragments, including the server(s) thatserviced the assembling device before being identified as problematic.

In one embodiment, approximately random reselections of servers areperformed occasionally, even if all currently servicing servers arefunctioning correctly. In this case, the assembling device may select afew servers from the current set, to be randomly replaced. In oneembodiment, functioning servers are kept throughout several segmentretrieval cycles, and potentially for the entire delivery cycle of asegmented content.

In one embodiment, a method for reselecting one or morefractional-storage CDN servers on-the-fly, comprising: pullingerasure-coded fragments from the servers; estimating the servers' load,latency, network congestion, and packet loss; and operating a fuzzyalgorithm on the estimations in order to replace at least one of theservers with at least one other fractional-storage server. Optionally,the method further comprising operating the fuzzy algorithm based onmeasurements of many assembling devices and recommendations receivedfrom a central server. Optionally, the method further comprisingreplacing the servers quickly after missing a fragment. And optionally,the fuzzy algorithm weighs many possible solutions and converges to asufficient one.

In one embodiment, a distributed system is located in a few to dozens ofdata centers (also known as server farm or datacenter), located close toor on the Internet backbone, together housing at least 100fractional-storage CDN servers. The servers store erasure-codedfragments associated with approximately sequential segments of streamingcontents, with a storage gain of at least 5, and transmit the storedfragments on demand to assembling devices approximately according to thesequential order of the segments. In many cases, the data centersprovide a convenient place to place the CDN servers close to or on theInternet backbone. A data center can be also a collocation center, or anInternet Exchange Point. In one example, a single data center can housemany fractional-storage CDN servers.

In one example, a streaming system comprising at least several hundredsof fractional-storage CDN servers located close to or on the Internetbackbone, storing erasure-coded fragments encoded with a redundancyfactor greater than one, and associated with approximately sequentialsegments of streaming contents. At least 100,000 assembling devicesconcurrently obtain fragments from the CDN servers, wherein the systemachieves efficient load balancing and fault tolerance between thevarious CDN servers by determining for each of the assembling devicesfrom which servers to obtain the fragments.

In one example, a system comprising at least 1,000 fractional-storageCDN servers is connected to the public Internet. The servers storeerasure-coded fragments associated with approximately sequentialsegments of streaming contents, with a storage gain greater than 5, andtransmit the stored fragments on demand to assembling devicesapproximately according to the sequential order of the segments. Whereinthe aggregated bandwidth utilized by the servers for transmitting thefragments to the assembling devices exceeds 1 Giga bit per second timesthe number of the CDN servers. In one optional example, the systemcomprises at least 10,000 fractional-storage CDN servers and theaggregated bandwidth utilized by the servers exceeds 10 Giga bit persecond times the number of the CDN servers.

The term “redundancy factor” as used herein denotes the following ratio:(total size of the unique erasure-coded fragments generated from asegment and actually stored on the servers)/(size of the segment).

Assuming all segments have approximately the same size and all fragmentsgenerated from the segments have approximately the same size (withoutlimiting any of the embodiments), the term “storage gain” as used hereindenotes the following ratio: (size of a segment)/(size of anerasure-coded fragment). If the server stores more than oneerasure-coded fragment per segment, the storage gain denotes thefollowing ratio: (size of segment)/((size of erasure-codedfragment)*(number of stored erasure-coded fragments per segment)).

In one embodiment, a real-time proxy server located at or close to anedge of the Internet, configured to obtain erasure-coded fragments fromat least one CDN server located close to or on the Internet backbone. Ifthe proxy server has less fragments than needed to reconstruct asegment, the proxy obtains the remaining fragments from at least onefractional-storage server having much lower latency to the proxy thanthe backbone servers.

FIG. 22 (without the fragments marked with dashed lines) illustrates oneexample of distributing the erasure-coded fragments to ‘M’ CDN servers399 a to 399(M), connected to a network 300. Encoded fragments 310 a to310(M) of a first segment are sent for storage in servers 399 a to399(M) respectively. Similarly, erasure-coded fragments 320 a to 320(M)of a second segment are sent for storage in servers 399 a to 399(M)respectively. In addition, other erasure-coded fragments associated withother segments of other contents, illustrated as erasure-coded fragments390 a to 390(M), are sent for storage in servers 399 a to 399(M)respectively. The number of unique erasure-coded fragments from eachsegment that are stored on the servers (399 a to 399(M)) is equal to Min this example, where M may be smaller than the maximum number ofunique erasure-coded fragments, meaning that only a subset of thepotential erasure-coded fragments are actually stored. It is alsopossible to store the maximum number of unique erasure-coded fragments,or store more than one unique erasure-coded fragment per segment perserver. The network 300 may be the Internet for example, or any otherdata network connecting multiple nodes, such as a private IP network, ora Wide Area Network (“WAN”). In one embodiment, the fragments markedwith dashed lines illustrate one example where (N-M) additional serversare added to the array, and (N-M) new unique erasure-coded fragments persegment per content (310(M+1) to 310(N), 320(M+1) to 320(N), and390(M+1) to 390(N)) are generated and added to the array. In oneembodiment, only M out of the maximum possible erasure-coded fragments(L) are actually generated for storage in the first place. In oneembodiment, when the additional N-M erasure-coded fragments are neededfor storage (e.g., when additional servers are made available), theremainder of the N-M erasure-coded fragments are actually generated. Anytime that additional unique erasure-coded fragments are needed, thisprocess of calculating the additional erasure-coded fragments isrepeated, up to the point that all L possible erasure-coded fragmentsare used.

In one embodiment, and especially when using rateless coding, L may bechosen as a sufficiently large number to account for any realisticfuture growth of the server array. For example, a segment of 96 Kbytesis expanded using a rateless code with a ratio of 1 to 2̂16 originalsymbols to encoded data, into an encoding symbol of potential size 6.29GBytes. Assuming a 1500 Bytes erasure-coded fragment size, thenpotentially 4.19 million unique erasure-coded fragments can begenerated. Now, it is safe to assume that for all practical uses, theserver array will not grow to more than 4.19 million nodes, and maycontain several thousands of servers, meaning that the encoded data canbe used in all cases where additional unique erasure-coded fragments areneeded, by generating new erasure-coded fragments out of the segment.Optionally, a server may store erasure-coded fragments for only some ofthe segments.

In one example of redundancy factor and storage gain (without thefragments marked with dashed lines), server 399 a stores onlyerasure-coded fragment 310 a from a first segment, erasure-codedfragment 320 a from a second segment, and erasure-coded fragment 390 afrom a third segment. Assuming that: (i) the segment size is 1024Kbytes; (ii) the segment is encoded using erasure code into a 4096 KByteencoded segment; (iii) the encoded segment is segmented into 256erasure-coded fragments of size 4096/256=16 KByte; and (iv) theerasure-coded fragments are stored on 256 servers (M=256); it turns outthat each server stores only a 1/64 portion of the original size of thesegment. This means that each server can manage with only 1/64 of thestorage requirements in comparison to a situation where it had to storethe entire segment. In addition, there are 256 erasure-coded fragmentsaltogether from each encoded segment, meaning that an assembling devicethat is assembling the erasure-coded fragments from the servers needonly select slightly more than 64 erasure-coded fragments in order tocompletely reconstruct the segment, and it can select whichever slightlymore than 64 erasure-coded fragments it desires out of the 256 possiblyavailable. The redundancy factor in this example is approximately256/64=4. All contents in this example enjoy a factor of 64 in storagegains, meaning that server 399 a, for example, stores only 1/64 of theinformation associated with the first segments and any additionalsegments belonging to other contents. In one example, each serversupports high volume storage of between about 500 GByte and 500 TBytes,optionally utilizing hard drive, Solid State Drive, or any other highvolume storage device(s). In these cases, each server may store manymillions of erasure-coded fragments, associated with millions ofsegments, belonging to hundreds of thousands of different contents, andpossibly more.

In one embodiment, new content initially encoded with a low redundancyfactor is distributed to an initial number of fractional-storageservers. As the content is distributed to more servers, additionalunique fragments are encoded and therefore the redundancy factorincreases. Optionally, as the content's popularity increases, and/or asthe load on the fractional-storage servers increases, the redundancyfactor is increased, and vice versa.

In one embodiment, multiple unique erasure-coded fragments per segmentof a new content are distributed to an initial number offractional-storage servers with a low storage gain (i.e. each serverstores multiple unique erasure-coded fragments per encoded segment). Asthe content is distributed to more fractional-storage servers, some ofthe erasure-coded fragments stored on the initial number offractional-storage servers are removed and thereby the storage gain isincreased. Optionally, as the demand for the content increases, thestorage gain is decreased, and vice versa.

FIG. 23 illustrates three examples (each depicted by one of the columnsA-C) of changing the redundancy factor according to the demand. Column Aillustrates one simplified example of a storage array including 16servers (1001 to 1016). Each server stores up to 2 differenterasure-coded fragments, and can service an erasure-coded fragmenttransmission bandwidth of up to B. Assuming three contents (#1, #2, and#3) processed to segments and erasure-coded fragments with a storagegain of 4.

Assuming content #1 is the most popular, and requires a peak bandwidthof 11×B. Since each server can service up to bandwidth B, at least 11servers are needed to service content #1 bandwidth requirements. Content#1 is therefore encoded into 11 unique erasure-coded fragments persegment, illustrated as group g1 of erasure-coded fragments stored onservers 1001 to 1011. Out of these 11 erasure-coded fragments, it issufficient to obtain slightly more than 4 erasure-coded fragments inorder to reconstruct a segment of content #1. Therefore, the resultingredundancy factor of the stored fragments associated with content #1 isapproximately 11/4=2.75. Content #2 requires less bandwidth, and manageswith a peak of 7×B. It is therefore encoded into 7 unique erasure-codedfragments per segment, illustrated as group g2 of erasure-codedfragments on servers 1010 to 1016. Therefore, the redundancy factor ofthe stored fragments associated with content #2 is 7/4=1.75. Content #3requires a peak bandwidth of 5×B, but for some reason (for example,being a more critical content), it is encoded into 14 erasure-codedfragments per segment, illustrated as group g3 of erasure-codedfragments on servers 1001 to 1009 and 1012 to 1016. Therefore, theredundancy factor of the stored fragments associated with content #3 is14/4=3.5. This concludes the storage availability of the servers in thisexample, as every server stores two erasure-coded fragments.

Column B illustrates an example where content #2 becomes more popularthan content #1, and therefore requires more bandwidth and hence more ofa redundancy factor. This is achieved by eliminating 5 erasure-codedfragments associated with content #1 that were previously stored onservers 1001 to 1005, and replacing them with 5 new unique erasure-codedfragments g4 associated with content #2. This brings the total number oferasure-coded fragments per segments of content #1 and #2 to 6 and 12respectively. In column C, new content #4 is stored on servers 1001 to1003 and 1014 to 1016 (illustrated as g5), by eliminating 3erasure-coded fragments of content #1 and 3 erasure-coded fragments ofcontent #2.

Throughout the examples of FIG. 23, a record of “what erasure-codedfragments are stored where” may be: (i) kept in each of the servers 1001to 1016. In this case, when an assembling device is assembling content#2, it will send a query to servers 1001 to 1016, asking which one isstoring erasure-coded fragments of content #2; (ii) kept in a controlserver. In this case, an assembling device will ask the control serverto send back a list of all servers storing erasure-coded fragments ofits required content.

With reference to FIG. 23, the following embodiments discuss variousalternative ways to distribute the erasure-coded fragments among thevarious servers.

In one embodiment, the erasure-coded fragments associated with a firstsegment of a first content are stored on exactly the same servers as theerasure-coded fragments associated with a second segment of the firstcontent. In one embodiment, the erasure-coded fragments associated withthe first and the second segments of the first content are stored ondifferent servers.

In one embodiment, different servers have different maximal bandwidths.The process that assigns erasure-coded fragments to servers takes thatinto account, and selects the different servers and the number oferasure-coded fragments per segment such that the integration ofbandwidth over all selected servers yields the desired content's peakbandwidth.

In one embodiment, different servers have different bandwidth quota percontent. The process that assigns erasure-coded fragments of a newcontent to servers takes that into account, and selects the differentservers and the number of erasure-coded fragments per segment such thatthe integration of bandwidth quotas over all selected servers yields thedesired content's peak bandwidth.

In some embodiments, each server stores a different number oferasure-coded fragments, and has a different bandwidth quota percontent. The following examples describe possible processes forassigning erasure-coded fragments of a new content to servers. A firstexample including: (i) Identifying all servers with enough storage spaceto accommodate the new erasure-coded fragments. (ii) Sorting theidentified servers by bandwidth quota (optionally, highest to lowest).(iii) Integrating the bandwidth quotas from the sorted list, up to thepoint where the resulting integrated bandwidth equals the content'sdesired bandwidth. All of the servers in the list up to the equalitypoint are then selected as hosts for the new erasure-coded fragments. Asecond example including: (i) Identifying all servers with enoughstorage space to accommodate the new erasure-coded fragments. (ii)Approximately randomly selecting servers out of the identified list, upto the point where the resulting integrated bandwidth equals the desiredbandwidth for the content. All of the chosen servers are then selectedas hosts for the new erasure-coded fragments. A third example including:(i) Identifying all servers with available bandwidth quota for the newerasure-coded fragments. (ii) Sorting the identified servers byavailable storage space (available to unavailable). (iii) Integratingthe bandwidth quotas from the list sorted by storage, up to the pointwhere the resulting integrated bandwidth equals the desired bandwidthfor the content. All of the servers in the list up to the equality pointare then selected as hosts for the new fragments.

In some embodiments, a broadcast-like effect is achieved by distributingto and retrieving from fractional-storage servers a broadcastchannel/live content in real time, using a combination of real timedistribution and real time retrieval techniques. In a broadcast-likeeffect, a given channel or content for broadcasting is distributed to atleast one assembling device, optionally by means of pushing relevantfragments to the assembling device, or by pulling the relevant fragmentsby the assembling device, and potentially to many assembling devices atapproximately the same time, which creates a similar effect totraditional broadcasting.

FIG. 24 illustrates one example of creating a broadcast-like effect(i.e. retrieving the content while it is distributed). Streaming content700 a, which may be ready in advance or received on-the-fly, is to bereceived and presented by multiple assembling devices at approximatelythe same time. Content 700 a is segmented into segments on-the-fly, suchthat the first segment 710 a is ready shortly after the data isavailable, and subsequent segment 710 b is ready right after that.Segments 710 a and 710 b are sequentially encoded into erasure-codedfragments 782 a and 782 b correspondingly, such that the average rate ofencoding segments into erasure-coded fragments does not fall below theaverage rate of introducing new segments (as content 700 a is beingreceived for broadcast).

As the erasure-coded fragments 782 a are ready, they are distributed 783a to the fractional-storage servers. Subsequent erasure-coded fragments782 b are similarly distributed 783 b to the servers, such that theaverage rate of distributing the erasure-coded fragments associated witheach segment does not fall below the rate of introducing new segments(or in other words, such that there is approximately no piling-up ofundistributed segments). Optionally, the erasure-coded fragments 782 aare also distributed 784 a by the servers to bandwidth amplificationdevices at an average distribution rate per segment that does not fallbelow the average rate of introducing new segments.

The assembling devices obtain erasure-coded fragments 785 a associatedwith segment 710 a from the fractional-storage servers, and optionallyalso from the bandwidth amplification devices. Subsequent erasure-codedfragments, such as 785 b associated with segment 710 b, are obtained atan average rate that does not fall below the average rate of introducingthe new segments. The segment 710 a is then reconstructed from theobtained erasure-coded fragments 785 a. The subsequent segment 710 b isreconstructed from the obtained erasure-coded fragments 785 b, such thatreconstructing each segment is performed at an average rate that doesnot fall below the average rate of introducing the new segments.

Then, the reconstructed segments are presented, optionally on-the-fly,as reconstructed content 700 b. In one embodiment, the entire processend-to-end is performed in real time, such that the presentation of 700b starts at T2 minus T1 after the availability of content 700 a, andsuch that the delay of T2 minus T1 (between the availability of newsegments and their subsequent presentation by the assembling device) iskept approximately constant throughout the entire presentation of thestreaming content 700 b, once begun.

In one example, the content 700 a is a 4 Mbps video stream, and thesegment size is 96 Kbytes, meaning that new segments 710 a, 710 b aremade available at a rate of one every 0.19 seconds. Assuming that eachprocess as described takes 0.19 seconds, and that all processes areperformed sequentially (with no overlapping in time, which may bepossible for some of the processes), then the accumulated process time,which includes 710 a, 782 a, 783 a, 784 a, 785 a and 710 a, takes about6×0.19=1.14 seconds. This means that an assembling device may begin withcontent presentation 1.14 seconds after the content is first madeavailable to the system.

Still referring to FIG. 24, in one embodiment, the fragments areobtained from the servers using multiple sub-transmissions, such thateach transmitting server sends a fraction of the needed fragments to theassembling device, according to the sequential order of segments. Eachsub-transmission transmits the fragments approximately at a rate atwhich the fragments are being created on-the-fly from segments of thecontent to be received by the assembling device. According to anotherembodiment, the fragments are obtained from the servers using fragmentrequests made by the assembling device using a fragment pull protocol.

The Audio/Video compression utilized in creating content 700 a is notnecessarily a fixed rate compression, meaning that the various resultingsegments do not necessarily contain the same amount of presentationtime.

In one embodiment, once starting to retrieve a broadcast-like stream,the assembling device may use one of the following methods tosynchronize the retrieval of the stream's segments with the ongoingavailability of new segments of the stream: (i) The assembling deviceretrieves additional segments such that the average rate of obtainingnew frames approximately equals the average rate of presenting frames.(ii) The assembling device retrieves additional segments such that itdoes not try to retrieve segments that are not yet indicated as beingavailable. And (iii) The assembling device retrieves additional segmentsso as to approximately maintain a constant distance (in segments)between the most currently available segment and the segment currentlybeing retrieved.

In one embodiment, the assembling device presents the broadcast-likestream at approximately the same frame rate as the rate of producing newframes for the broadcast-like stream. In one example, the frame rate isconstant throughout the stream, such as the case of fixed 24, 25, 50, or60 frames per second.

In one embodiment, the assembling device obtains an indication regardingthe most newly available segment (per specific broadcast-like stream)for retrieval. The assembling device then starts to retrieve from themost newly available segment. In one example, the most newly availablesegment is the last segment that was distributed to thefractional-storage servers. In another example, the most newly availablesegment is a segment that was recently distributed to thefractional-storage servers, but wherein there are newer distributedsegments, which are not yet indicated as being available.

In one embodiment, the broadcast-like stream is of a pre-recordedcontent, such that it is possible to distribute the entire content tothe fractional-storage servers, and after any period of time allow thereal time consumption of the content by any number of assemblingdevices. In such a case, an indication is made to the assembling devicesregarding the real time allowance to retrieve the related segments. Theallowance can start at a certain point in time (which corresponds to thebeginning of the broadcast-like “transmission”) for the first segment,and then the allowance may continue for subsequent segments, at a ratethat approximately corresponds to sustaining the frame rate of thebroadcast-like stream.

In one embodiment, the fractional-storage system is approximatelyinsensitive to the mixture of the consumed contents as long as theaggregated throughput is below the total throughput of thefractional-storage servers.

FIG. 25 illustrates one example of a server array, including Nfractional-storage servers (399 a to 399(N)), and storing content A,which includes erasure-coded fragments 310 a to 310(N), and content B,which includes erasure-coded fragments 320 a to 320(N). Each server isconnected to the network 300 with a fragment delivery bandwidthcapability B 339. Therefore, the N servers have an aggregated bandwidthof B×N. A first group of assembling devices 329 a consumes content A atan average bandwidth Ba 349 a. A second group of assembling devices 329b consumes content B at an average bandwidth Bb 349 b. Since all of theservers participate in the transmission of the two contents, the firstand second groups can potentially consume all server bandwidth, up tothe limit where Ba+Bb=N×B, with any ratio of demand between the firstand second contents, and with no special provisions to be made whenstoring the erasure-coded fragments related to the two contents in thefractional-storage server array.

FIG. 26 illustrates the case where the first group 328 a, which consumescontent A, becomes larger than 329 a, with a larger bandwidth Ba 348 a.The second group 328 b, which consumes content B, becomes smaller than329 b, with a smaller bandwidth Bb 348 b, such that Ba is about the sameas Bb. In this case, the array can still be exploited up to theaggregated bandwidth, since, as before, Ba+Bb can still be almost ashigh as N×B. FIG. 27 illustrates the case where the first group hasdisappeared, allowing the second group 327 b, which consumes content B,to extract an aggregated bandwidth of Bb 347 b that can potentiallyreach the limits of the server array, such that Bb=N×B. Again, this isachieved without updating the erasure-coded fragments associated withcontent A and content B, and without using inter-server interaction.

In some embodiments, the ability to utilize the aggregated bandwidth ofapproximately all of the participating servers, for the delivery ofabout any mixture of contents with about any mixture of contentbandwidth demand, is made possible by one or more of the following: (i)each assembling device selecting a subgroup of the least loadedfractional-storage servers from which to retrieve the necessary numberof erasure-coded fragments to reconstruct a segment or several segments(least-loaded server selection criterion); or (ii) each assemblingdevice approximately randomly selecting a subgroup from which toreconstruct a segment or several segments, such that when manyassembling devices select at random, the various fractional-storageservers are selected approximately the same number of times (or inproportion to their available resources, such as unutilized bandwidth),which in turn balances the load between the participating servers(random server selection criterion). It is noted that (i) the selectionsmay be made by either the assembling devices themselves, or may be madefor the assembling devices by a control server, which then communicatesthe selections to each of the assembling devices; (ii) the selectionsmay be made approximately for each segment, or for a group of segments,or only once per content at the beginning of the content; (iii) someassembling devices may use an approximately random server selectioncriterion, while other assembling devices may use least-loaded serverselection criterion; (iv) the least-loaded selected servers may beselected out of a portion of all available fractional-storage servers.For example, the least-loaded servers may be selected fromfractional-storage servers with low latency response or with low hopcount to the assembling device; (v) the least-loaded servers may includeservers having the most unutilized bandwidth. Additionally oralternatively, it may include servers having any unutilized bandwidthleft to serve additional assembling devices; (vi) an approximatelyrandom or least-loaded selection of servers may be made such that allservers are selected to determine a subgroup, or it can be made suchthat every time selections are made, only some servers are selected,while the others remain as before. In these cases, the assembling deviceruns a process in which only a small portion of the servers currently inthe serving subgroup are reselected. In the case of approximately randomselection, the assembling device may randomly select the number ofservers in the serving subgroup for random selection (reselection inthis case, since they are replacing other servers already in the servingsubgroup of the specific assembling device), such that eventually, overtime, all servers within the serving subgroup have the chance to berandomly reselected. In the case of least-loaded server selection, onlythe most loaded servers within the serving subgroup may be selected andreplaced by less-loaded servers.

FIG. 28 illustrates one embodiment of using the entire aggregatedbandwidth of the fractional-storage servers for delivering multiplecontents. Approximately any number of contents having any mixture ofbandwidth demand per content may be delivered, as long as the aggregatedbandwidth demand does not exceed the aggregated bandwidth of thefractional-storage servers. In one example, broadcast-like streams 3101,3102, and 3103 are delivered to multiple assembling devices via multiplefractional-storage servers. Each stream is a live TV channel carryingmultiple TV programs. For example, stream 3101 comprises TV programs3110 to 3112, each spanning a specific time interval. The other streamscomprise of multiple TV programs as well. Before time T1, stream 3130has a bandwidth demand of 3130′ (meaning that all assembling devicesthat are currently retrieving stream 3130′ use a total bandwidth of3130′ out of the fractional-storage servers). The other streams 3120 and3110 have bandwidth demands of 3120′ and 3110′ respectively. The totalbandwidth demand of the three streams 3130′+3120′+3110′ does not exceedthe aggregated bandwidth of the fractional-storage servers 3150, andtherefore all streams are fully delivered to the assembling devices. Theload of the three streams is spread approximately equally among theparticipating fractional-storage servers, optionally because of amechanism that selects the least-loaded servers to serve each assemblingdevice, and/or a mechanism that approximately randomly selects serversto serve each assembling device. At time T1, TV program 3120 ends, andTV program 3121 starts. Program 3121's demand 3121′ is higher than theprevious demand 3120′, and therefore a higher aggregated bandwidth isdrawn from the fractional-storage servers. Still, the aggregatedbandwidth demand of all three streams (3130′+3121′+3110′) is lower thanthe maximum possible 3150, and therefore the newly added bandwidthdemand is fully supported by the servers. Optionally, the additionaldemand created by TV program 3121 (3121′ minus 3120′) is caused by theaddition of new assembling devices that join stream 3102 and retrievingadditional erasure-coded fragments. Additionally or alternatively, theadditional demand created by TV program 3121 is caused by a higherbandwidth demand of TV program 3121, such as 3D data or higherresolution. Newly added assembling devices may choose fractional-storageservers from which to retrieve, according to a least-loaded serverselection criterion and/or an approximately random server selectioncriterion, and therefore the total load is still spread approximatelyequally among the participating servers. At time T2, TV program 3110ends, and a new program 3111 begins, which is less popular, andtherefore creates a lower bandwidth demand 3111′. The result is adecrease in the total delivered bandwidth. At time T3 TV program 3130ends, and TV program 3131 starts with a higher bandwidth demand of3131′. At time T4 both TV programs 3111 and 3121 end, and two newprograms 3112 and 3122 start. TV program 3112 is highly popular andtherefore generates a large bandwidth demand 3112′. Program 3122 is notpopular, and therefore generates a limited bandwidth demand 3122′. Someof the additional bandwidth needed by program 3112 is taken from serversthat stop serving assembling devices previously retrieving program 3121,such that the aggregated bandwidth of all three streams(3131′+3122′+3112′) is still below the maximum possible bandwidth 3150,despite the fact that program 3112 is generating a large bandwidthdemand. This example illustrates how the fractional-storage serverssupport almost any demand mixture, as long as the aggregated demand ofall streams is kept below the aggregated maximum capacity of the servers3150. Consequently, the distribution of all of the streams to thefractional-storage servers is approximately unrelated to the changes inbandwidth demand for programs carried by each stream; each stream can beregarded as a sequence that is segmented, erasure-encoded, anddistributed to the participating servers. There is no need to accountfor demand variations during the distribution of each stream, nor isthere a need to know in advance the bandwidth demand for each stream orfor each program within each stream. It is noted that the demandvariations are illustrated as instant variations, but may also begradual and may occur during a program and not necessarily when oneprogram ends and the other begins.

In one embodiment, the assembling device categorizes the servers intotwo categories: (i) fastest responding servers, and (ii) slowerresponding servers, and approximately avoids initial fragment requestsfrom the fastest responding servers, such that if additional fragmentsare needed, they are quickly retrieved from the fastest respondingservers. Avoiding retrieval from the fastest responding servers wheninitially requesting the fragments of a segment increases the chances ofretrieving a substitute fragment, needed to compensate for the lostfragments, from the fastest responding servers, and enables fastcompensation that is needed for fast presentation of the streamingcontent. Categorizing the servers may be performed by registeringmeasured latencies of servers responding to fragment requests by theassembling device.

In one embodiment, a plurality of fractional-storage servers, which maybe located almost anywhere around the globe, configured to storeerasure-coded fragments associated with segments of streaming content.An assembling device, which may be located almost anywhere around theglobe, configured to request, using a fragment pull protocol over theInternet, a set of fragments. The assembling device is furtherconfigured to compensate for lost fragments by requesting additionalerasure-coded fragments that are needed to reconstruct the segments.wherein the bandwidth of the streaming content is bounded approximatelyonly by the incoming bandwidth of the assembling device.

In one embodiment, fractional-storage CDN servers configured to storeerasure-coded fragments associated with approximately sequentialsegments of streaming content. An assembling device located at a pointfeaturing an average one-way network-related latency of more than 50milliseconds between the assembling device and the servers obtains afirst set of fragments, approximately according to the sequential orderof the segments, and compensates for lost fragments by obtaining asecond set of erasure-coded fragments that are needed to reconstruct thesegments. Wherein the bandwidth of the streaming content is boundedapproximately only by the incoming bandwidth of the assembling device.Optionally, the assembling device is configured to utilize a fragmentpull protocol to obtain the fragments. Optionally, the assembling deviceutilizes a push protocol to obtain the fragments.

In one embodiment, different quantities of erasure-coded fragments aregenerated per different segments. In one embodiment, some segments storedata that is considered more important than data stored in othersegments, and relatively more erasure-coded fragments are generated fromthe segments storing the more important data than from the segmentsstoring the less important data.

In one example, a compressed video content is segmented into segmentsstoring i-frames and segments storing p-frames. Optionally, all segmentsare approximately of the same size, and more erasure-coded fragments aregenerated from the segments storing the i-frames than from the segmentsstoring the p-frames. Alternatively, the segments storing the i-framesare shorter than the segments storing the p-frames, and approximatelythe same quantity of erasure-coded fragments are generated from thesegments storing the i-frames and from the segments storing thep-frames.

In one example, a DCT content is segmented into segments storing lowfrequencies and segments storing high frequencies. Optionally, allsegments are approximately of the same size, and more erasure-codedfragments are generated from the segments storing the low frequenciesthan from the segments storing the high frequencies, where in addition,the size of the erasure-coded fragments generated from the segmentsstoring the low frequencies is smaller than the size of theerasure-coded fragments generated from the segments storing the highfrequencies. Alternatively, the segments storing the low frequencies areshorter than the segments storing the high frequencies, andapproximately the same quantity of erasure-coded fragments are generatedfrom the segments storing the low frequencies and from the segmentsstoring the high frequencies.

In one embodiment, in order to reduce the time to play from requesting acontent until the content begins playing, or the time from jumping to aspecific location within the content until playing from that location,the assembling device may significantly increase its average consumptionrate of erasure-coded fragments for some time, for example, 2 to 50times higher than its steady state consumption rate of erasure-codedfragments. When many assembling devices simultaneously attempt toretrieve the same content using high consumption rate of erasure-codedfragments, some servers may become saturated because of the peak in thedemand. Therefore, in one embodiment, the number of unique erasure-codedfragments a fractional-storage server can supply in such cases isincreased. Moreover, in one embodiment, the erasure-coded fragments areretrieved from nearby servers in order to achieve low latency; but thenearby servers may not store sufficient unique erasure-coded fragmentsper the required segments. Therefore, an extra quantity of erasure-codedfragments is generated from segments expected to require the higherconsumption rate of erasure-coded fragments, such as the segments at thebeginning of a content, and/or segments at some predefined trick playstart points. In one embodiment, the extra quantity of erasure-codedfragments is distributed among more servers. As a result, the load ofretrieving the erasure-coded fragments is distributed among moreservers, which in turn, weakens the peak effect.

FIG. 29 illustrates the process of generating a larger quantity oferasure-coded fragments in the vicinity of the fast start points. Thecontent 100 is segmented into segments 251. The segments 251 that are inthe vicinity of the one or more fast start points, marked in dashedlines, are encoded by the erasure encoder 252 into a larger quantity oferasure-coded fragments (illustrated by more rectangles in part 253),which may then be distributed 255 among fractional-storage servers. FIG.30 is a schematic view of generating erasure-coded fragments from thecontent 100, wherein larger quantities of erasure-coded fragments aregenerated in the vicinity of the fast start point(s).

In some embodiments, the content is segmented into a plurality ofsegments to enable beginning to play the content as it is beingobtained, and optionally enable trick play. The different segments mayor may not be of the same size.

The following embodiments discuss different methods for segmenting thecontent. In one embodiment, at least one portion of the content issegmented into multiple segments in sizes within a first size range, andthe remainder of the content is segmented into a plurality of segmentsin sizes within a second size range (additional size/s may be addedsimilarly). The sizes included in the second size are larger than thesizes included in the first size range. Pluralities of erasure-codedfragments are generated from each of the segments. The segments of sizeswithin the first size range are better suited for fast retrieval, andthe segments of sizes within the second size range are better suited forhigh-gain storage. In one example, the segments in sizes within thefirst size range belong to approximately the beginning of the content.In one example, the segments in sizes within the first size range belongto locations within the content requiring trick play access. In oneembodiment, the segments of the first type are encoded into fewerfragments than the segments of the second type. This allows a fastretrieval of the shorter segments.

In one embodiment, a first sub-group of the servers stores segments ofthe first type, and a second sub-group of the servers stores segments ofthe second type, whereby the first and the second sub-groups mayoverlap. In one example, the sub-group storing the short segmentscomprises a large number of servers, in order to facilitate high levelof availability and responsiveness.

In one embodiment, the segments of the first type are encoded with afirst redundancy factor, and the segments of the second type are encodedwith a second redundancy factor, where the first redundancy factor issignificantly higher than the second redundancy factor. In one example,the high redundancy factor allows the fragments of the short segment tobe available on a large number of servers. In one example, the fragmentsassociated with the first type of segments are stored on a significantamount of the servers, such that an assembling device can potentiallyretrieve a decodable set of fragments from nearby servers.

In one embodiment, an assembling device reconstructs segments ofstreaming content by obtaining, from fractional-storage servers,decodable sets of erasure-coded fragments associated with the first orthe second type of segments. Each type of segment requires differentamount of fragments in order to be decoded. The assembling deviceobtains the fragments according to information describing the positionof the different types of segments within the streaming content. In oneexample, the information contains the number of fragments needed todecode the different types of segments. In one example, content iscomposed of one initial short segment requiring 20 fragments forreconstruction, followed by 1,000 long segments, each requiring 200fragments for reconstruction. The assembling devices receive informationfrom a control server regarding the above structure, and obtain at least20 fragments for the first segment, followed by at least 200 fragmentsfor each additional segment.

In one example, the content 100 is a 1 GByte encoded H.264 file, storinga 2-hour motion picture, and is segmented into approximately 10,000segments of approximately 100 Kbytes each. In another example, thecontent 100 is a 4 MByte web-site information (HTML, FLASH, or any othercombination of information that encodes the presentation of a website),and is segmented into 4 segments of approximately 1 MByte each.

In one example, the content supports streaming presentation, and thesegments are small enough to enable presentation shortly after beginningthe reception of the first segment(s). For example, each segment mayinclude 96 KByte, allowing a 5 Mbps receiver to download the segment inapproximately 0.2 seconds, and optionally begin the presentation shortlythereafter. In one embodiment, the time to play is reduced by segmentingcertain portions of the content into smaller segments, while theremaining portions are segmented into larger segments. A smaller segmentcan be retrieved faster, while a larger segment may be better optimizedfor storage gain and/or efficient transmission.

In one embodiment, the short segments are 96 Kbytes in size, and thelong segments are 960 Kbytes in size. The redundancy factors used forencoding short and long segments into fragments are 100 and 5respectively. 1500 Bytes fragments are used for both sizes. The shortsegments are therefore encoded into (96K/1500)×100=6,400 fragments, fromwhich only about 64 are needed for reconstruction, and the long segmentsare encoded into (960K/1500)×5=3,200 fragments, from which only about640 are needed for reconstruction. Short segments are reconstructed morequickly than long ones, as they require fewer fragments to be decoded.Optionally, each fragment is stored on a different server, resulting ina storage gain of 64 for short segments, and 640 for long segments.

FIG. 31 illustrates one example in which the content 100 is segmentedinto segments, such that the first segment 104 a is smaller than theconsecutive segment 104 b, which is smaller than following segments 104c and 104 d. In another example, the content 100 is segmented intosegments, such that the first several segments (e.g. 104 aa and 104 bb,which are the same size), are smaller than consecutive segments (e.g.104 cc and 104 dd, which are the same size).

FIG. 32 illustrates one example in which the content 100 is segmentedinto cyclic sets of successive segments increasing in size. For example,105 b is equal or larger in size than 105 a, and so on, up to segment105 d; 105 f is equal or larger in size than 105 e, and so on, up tosegment 105 h. In one example, segment 105 e is equal in size to segment105 a. Point 105EP represents the ending of the first set, and thebeginning of the second set.

In one embodiment, segments are created on-the-fly, such as during alive event or when the content is made available to the segmentationprocess as an on-going stream. In one embodiment, the content supportsstreaming presentation, and the segments are of the small size, toenable content presentation shortly after beginning the reception of thefirst segment (or any other segment). In addition, the erasure-codedfragments are kept as small as possible, while still enabling efficienttransport over an IP network. For example, each erasure-coded fragmentis about 1500 Bytes and can be transported using one IP packet.

It is to be noted that streaming content may also be manifested as anintermediate product of a process. For example, in a case where a videocamera outputs erasure-coded fragments that can be decoded intostreaming content, the intermediate data from which the erasure-codedfragments are generated is considered to be streaming content (even ifthe video camera does not output that intermediate data). Moreover,streaming content may include: content that is produced and thenimmediately transmitted to a receiving server, content that is producedbut stored for any length of time before being transmitted to areceiving server, content that is transmitted to a receiving server andthen immediately sent from the receiving server to a client, contentthat is transmitted to a receiving server, then buffered for some timeat the receiving server and then sent from the receiving server to aclient, content that is solely played at a client, and content that ismanipulated or changed or reacted to at the client while a continuationof the content is still being played at the client.

FIG. 33 illustrates one embodiment, wherein segment 101 a of content 100is encoded into erasure-coded fragments 390 a to 390(M), such that anysufficient subset of the fragments can be used to reconstruct segment101 a. Fragments 390 a to 390(N) are stored in fractional-storageservers 399 a to 399(N) respectively, and fragments 390(N+1) to 390(M)are stored in streaming server 399S. In one example, fragments 390(N+1)to 390(M) form a group of fragments which are sufficient to reconstructsegment 101 a. Subsequent segments 101 b to 101 j of content 100 may besimilarly encoded into additional fragments stored on the servers (notillustrated). Assembling device 309 uses two different protocolsapproximately simultaneously to retrieve fragments for segmentreconstruction: (i) a push protocol, and (ii) a fragment pull protocol.The push protocol 301S is used to deliver fragments 390(N+1) to 390(M)to assembling device 309. The push protocol may be RTP based orTCP-connection based, or any other type of transmission that does notrequire assembling device 309 to explicitly ask for each of fragments390(N+1) to 390(M). In one example, fragments 390(N+1) to 390(M) aredelivered to the assembling device using a single RTP stream 301S, suchthat upon reception of the fragments from the stream, the assemblingdevice can immediately reconstruct segment 101 a. The fragment pullprotocol is used by the assembling device to retrieve additionalfragments that may be needed to reconstruct segment 101 a if one or morefragments out of fragments 390(N+1) to 390(M) fail to reach theassembling device. In one example, fragment 390(N+2) fails to reach theassembling device due to Internet packet loss conditions (referred to asfragment loss). The assembling device, after concluding that fragment390(N+2) is missing, uses a fragment pull protocol to retrieve asubstitute fragment out of one of the fractional-storage servers 390 ato 390(N), and uses this fragment to complete the reconstruction of thesegment 101 a (any one of fragments 390 a to 390(N) will do). Forexample, the assembling device chooses fragment 390 a as the oneadditional fragment, by requesting and receiving it 303 a from server399 a, using a fragment pull protocol. If more fragments out offragments 390(N+1) to 390(M) fail to reach the assembling device 309, itmay compensate by pulling substitute fragments from some or all ofservers 399 a to 399(N), illustrated as fragment pull protocol requestsand responses 303 a to 303(N)).

In one embodiment, the fragment pull protocol requests for additionalneeded fragments are not made to fractional-storage servers 399 a to399(N), but are rather made to server 399S. In this case, the assemblingdevice asks server 399S to retransmit the fragment which has failed toarrive. In this embodiment, only fragments that fail to reach theassembling device via the push transmission 301S cause an addedcommunication overhead in the form of explicit fragment pull protocolrequests, such that if no fragments are actually lost over transmission301S, there is no need for fragment pull requests 303 a to 303(N).

In some embodiments, the push protocol is implemented using one or moresub-transmissions. Optionally, a push protocol transmission isimplemented using multiple sub-transmissions, each transporting afraction of the fragments transmitted by the push protocol transmission.A sub-transmission may be transported using an IP stream such as RTP, anHTTPS session, or any other form of transporting a sequence of fragmentsbetween a source server and a destination assembling device.

In one example (not illustrated), the storage gain equals one and if onefragment fails to arrive, the assembling device has to access thespecific server storing the specific fragment, and request the specificfragment via a pull protocol. The push transmissions 301 d to 301 f maybe synchronous (such as all servers sending the fragments of eachsegment approximately at the same time), or may be asynchronous. In thelatter case, the arrival of different fragments associated with aspecific segment at the assembling device side may be spread over a longperiod. This may occur, as an example, when some push servers are fasterthan others are. In this case, the assembling device aggregates whateverfragments it can before presentation time of each segment, and thensupplements fragments using pull retrieval processes. A server that doesnot send fragments fast enough, and therefore approximately alwayscauses supplemental requests, can be asked to stop thepush-transmission. Another server may be asked by the assembling deviceto replace the slow server by initiating a new push-transmission.

In one embodiment, the push-transmissions carry more fragments thanneeded for segment reconstruction. In one embodiment, the pushtransmissions carry fewer fragments than needed for segmentreconstruction, and the remaining fragments are pulled by the assemblingdevice.

In one embodiment, an assembling device starts retrieving fragmentsusing only fragment pull protocol processes, and then, when concludingthat a specific server is responsive enough, instructs it to startsending a push-transmission for the remaining segments. In this case,the assembling device may start with pure pull-protocol based fragmentretrieval, and gradually switch to push-protocol transmissions, up tothe point that approximately all fragments are delivered usingpush-transmissions, and using the pull requests only as a means toovercome failure of obtaining specific fragments by the assemblingdevice. In one embodiment, the fragment pull protocol and the pushprotocol are used interchangeably to obtain enough fragments toreconstruct segments. In one embodiment, the assembling device may startto obtain fragments using a push protocol and then switch to a fragmentpull protocol. In one embodiment, the assembling device may use bothfragment pull protocol and push protocol to obtain fragments at the sametime, wherein the assembling device may change the ratio Fpull/Fpushon-the-fly to any value between zero and infinity, where Fpull denotesthe number of fragments associated with a certain segment that areobtained using a fragment pull protocol, and Fpush denotes the number offragments associated with the certain segment that are obtained using apush protocol.

In one embodiment, the assembling device uses a fragment pull protocolto start obtaining fragments needed to reconstruct at least one segmentneeded for fast-start playing of content, and then switches to a pushprotocol if and when possible. In this case, the fragment pull protocolprovides a fast response from servers, allow minimization of the timebetween a user's request and corresponding content playing. In oneexample, at least one segment needed for the fast-start playingcomprises enough data to enable continuous presentation of the streamingcontent, at least up to when a first fragment is obtained using the pushprotocol. In one example, the assembling device obtains the fragmentsassociated with the at least one segment approximately as fast as thebandwidth available to the assembling device allows, and then plays thecontent approximately as soon as enough segments, out of the at leastone segment, are reconstructed to allow doing so.

In the claims, sentences such as “wherein the assembling device isconfigured to use a fragment pull protocol to obtain the fragments” and“wherein the assembling device is configured to use sub-transmissions toobtain the fragments” are to be interpreted as open claim language.Therefore, an assembling device configured to use a fragment pullprotocol to obtain fragments may also obtain fragments usingsub-transmissions, and vice-versa.

FIG. 34 illustrates one embodiment of real time streaming contentretrieval from fractional-storage servers, wherein erasure-codedfragments 720 a to 720(K) are retrieved in a fast cycle, meaning thatseveral erasure-coded fragments are obtained approximately in parallel.As a result, the interval T2 minus T1 is more or less limited only bythe download bandwidth of the assembling device's modem. Referring tothe example of FIG. 14, T2 minus T1 can be reduced from 0.77 seconds to0.15 seconds, if the modem operates at 5 Mbps (instead of 1 Mbps).

In one embodiment, T1 to T2 represents a fragment fetch cycle thatcorresponds to the beginning of streaming content to be presented (inthat case, segment 710 a is the first segment of the content, andpresentation 700 corresponds to the beginning of the streaming content),or corresponds to a certain point within the streaming content to bepresented starting this point onwards (in that case, segment 710 a is asegment within the content, and presentation 700 corresponds to playingthe content starting not from the beginning, but rather from segment 710a, located somewhere within the content). This is also known as trickplay. In one embodiment, erasure-coded fragments 720(a) to 720(K) areobtained such as to result in approximately a maximum utilization of thedownload capabilities of the assembling device, and such that the rateof requesting erasure-coded fragments results in a data arrival ratethat on average utilizes the assembling device's maximum downloadbandwidth.

In one embodiment, the fragment pull protocol request includes apriority indication. A high priority indication means that the serversshould give a preference to responding with a fragment transmission.High priority requests are served before other requests. Optionally,high priority requests are served even if the server's bandwidth quotais exceeded. In one embodiment, the high priority requests are used bythe assembling devices for receiving priority in the reception of thefirst segment, or several first segments, in order to facilitate faststarting of content presentation after content request by the user(either when starting to play a content, or in trick play mode, whenstarting to play a content from a certain point).

FIG. 35 illustrates one embodiment of a fragment pull protocol.Assembling device 861 (also represented by protocol diagram element 810b) obtains erasure-coded fragments from fractional-storage servers 899 ato 899(N) (also represented by protocol diagram element 898), utilizingthe following steps: (i) deciding 810 a which segment to retrieve; (ii)device 861 sending requests to some of the fractional-storage serversfor erasure-coded fragments associated with the desired segment. Forexample, requests 880 a to 880(K) for erasure-coded fragments 890 a to890(K), from servers 899(a) to 899(K), correspondingly; and (iii) theservers respond by sending the requested erasure-coded fragments. Forexample, servers 899 a to 899(K) send 881 a to 881(K) erasure-codedfragments 890 a to 890(K) to device 861. The fragment request andreceipt process begins at T1 c and ends at T1 d. At time T1 d, device861 has enough erasure-coded fragments (K) to reconstruct the segmentselected at 810 a. In one embodiment, the process from T1 c to T1 doccurs in real time, in support of streaming content presentation.

The term “fragment pull protocol for high latency” as used hereindenotes a protocol enabling an assembling device to request one or morefragments from one or more providing sources, wherein the time totransmit the one or more fragments in response to the assembling devicerequest, through the slowest communication link connecting theresponding source and the assembling device, is smaller than the roundtrip communication delay between the assembling device and theresponding source, excluding the processing time of the providingsource. For example, if the round trip communication delay betweenIsrael and the USA is about 200 ms, the assembling device requests onefragment sized about 1500 bytes, and the slowest communication link isan ADSL line connecting the assembling device at 1.5 Mbps, then the timeit takes to transmit the requested fragment through the slowestcommunication link is about 1500*8/1500000=8 ms, which is much smallerthan the round trip delay. Many of the disclosed embodiments usingfragment pull protocol may use fragment pull protocol for high latencyfor retrieving the fragments.

In one embodiment, more fragments than needed to reconstruct a segmentare requested, such that the additional requested fragmentsapproximately compensate for fragment failure conditions. If,statistically, F fragment requests are expected not to result in thereception of a fragment (i.e. fragment loss), out of a total number ofK+F fragment requests (wherein K is the minimal number of fragmentsneeded to reconstruct a segment), then it is possible to request K+Ffragments instead of just K. In one embodiment, more than K+F fragmentsare requested, since the quantity of the received fragments is astatistical variable. In this case, K+F+S fragments are requested,wherein S is a safeguard amount of additional requests to assure that atleast K fragments are received. In one embodiment, the fragment loss Fchanges over time, and the assembling device handles the change byincreasing or decreasing the number of fragments requested per segment.In one embodiment, the assembling device may determine F based onprevious fragment failure rates.

In one embodiment, requesting K+F+S fragments for a segment will almostalways result in the reception of at least K fragments, and thereforethe assembling device may request K+F+S without being concerned aboutwhich fragment has not arrived, and without trying to activelycompensate for fragment failures by issuing additional fragmentrequests. In this case, the assembling device requests the fragments inan “open loop” fashion, meaning that it requests the K+F+S fragments,and moves on to another segment. In one embodiment, even when requestingK+F, or K+F+S fragments per segment, it is still possible not to receivethe needed K fragments. Therefore, the assembling device may compensatefor undelivered fragments by issuing additional fragment requests (a“closed loop” operation).

In one embodiment, the K+F, or K+F+S fragment requests are issuedapproximately in parallel, in order to achieve the fastest responsepossible for reconstructing a segment. In this case, the fragments startto arrive at the assembling device a short while after being requested,such that as soon as at least K out of the requested fragments arrive,the assembling device may immediately proceed with reconstructing thesegment.

In one embodiment, an assembling device may aggregate several fragmentrequests into one message. The aggregated message is then sent to afractional-storage server, possibly in a payload of a single packet, andoptionally in order to conserve outgoing bandwidth and/or to reduce thenumber of packets needed to convey the requests. The fractional-storageserver may then read the aggregated message and act accordingly bysending a plurality of fragment responses to the assembling device. Thefragment responses may include one fragment at each payload, as is thecase of responding to a single fragment request, or it may include anaggregated response including multiple fragments at each payload.

In one embodiment, multiple segments of content, which, in one example,is streaming content, are reconstructed by an assembling deviceretrieving multiple erasure-coded fragments associated with the multiplesegments. Since a fragment request does not always result in a receptionof the fragment, some requested fragments may fail to arrive at theassembling device. Therefore, the assembling device checks (from each ofthe segments for which fragments have already been requested) whichrequested fragments have failed to result in a correct reception of afragment. For each such failure, the assembling device issues anadditional request for a fragment. The additional requests areassociated with segments for which fragments have already been requestedbefore, and therefore, in one example, the resulting fragment retrievalprocess includes the following two sub-processes: a first sub-process ofrequesting fragments associated with new segments to be reconstructed,and a second sub-process of requesting additional fragments needed tocomplement already requested fragments, in order to reconstruct thesegments. The first and second sub-processes work together, such thatthe second sub-process may complement fragments associated with a firstsegment, while the first sub-process runs ahead in an attempt to obtainfragments needed to reconstruct a second segment; wherein the secondsegment is located ahead of the first segment. The first and the secondsub-processes can also be described as two different quantities offragments being requested: a first quantity associated with the firstsub-process requests, and a second quantity associated with the secondsub-process requests.

In one embodiment, an assembling device may control the erasure-codedfragment reception throughput by controlling the rate of fragmentrequest. For example, each of n fragments has a known size S1 to Sn.Therefore, issuing n requests over a period of T will result in anaverage fragment reception throughput of (S1+S2 . . . +Sn)/T. In oneexample, if each fragment is 1500 Bytes, and 64 fragment requests areissued over a period of 0.5 seconds, then the average expected fragmentarrival throughput is (64×1500×8)/0.5=1.53 Mbps. The fragment requestsdo not need to be uniformly spread over the period of 0.5 seconds,although such a spread may result in a more stable throughput, whichmeans that less communication buffering will be needed. Using theabove-described rate-control technique may result in one or more of thefollowing: retrieving the content at a target fragment receptionthroughput; preventing communication buffer spill at the last milenetwork resulting from uncontrolled fragment requests; and/or reducingfragment loss due to averaging the fragment traffic.

In one embodiment, an assembling device transmits aggregated messages toa relay server, including the number of fragments needed per certainsegment, but without identifying the storage servers from whichfragments are to be requested. The relay server selects the appropriatestorage servers to which the fragment requests are to be transmitted,and transmits discrete or aggregated fragment requests, corresponding tothe number of fragments requested by the assembling device, to theselected storage servers. The storage servers receive the fragmentrequests from the relay server, and transmit the requested fragment tothe assembling device. The relay server may select the storage serversaccording to one or more criteria, as long as the selected storageservers store relevant fragments. Optionally, the relay server forwardsthe address of the assembling device to the selected storage servers,and/or adds the address of the assembling device to the fragmentrequests transmitted to the selected servers, in order to enable thestorage servers to transmit the fragment response to the assemblingdevice.

In one embodiment, shifting the process of selecting the storage serversfrom the assembling device to the relay server enables the design of arelatively thin and simple assembling device, having a relatively simplesoftware, since all the assembling device has to decide in order toissue an aggregated fragment request to the relay server is how manyfragments it needs per segment and, optionally, when it needs them.

In one embodiment, an assembling device transmits aggregated messages toa relay server, comprising general information regarding a portion ofstreaming content for which fragments are needed. Optionally, theportion of the streaming content comprises several consecutive segments.In one embodiment, the portion is defined by a starting point and anending point within the streaming content, and the relay server usesthese points to determine the actual segments comprising the portion.Then the relay generates and transmits the corresponding fragmentrequests to the relevant storage servers.

FIG. 36 illustrates one embodiment of fractional-storage servers 697 ato 697(N), wherein each server, or a group of servers, may be ownedand/or connected to the Internet in any combination and by differententities. The following 3 examples illustrate how the assembling devicesbalance the load on the fractional-storage servers.

In a first example, servers 697 a and 697 b, server 697 c, and servers697(N−1) and 697(N) are connected to the Internet 300 via first, second,and third Internet backbone operators (689 a, 689 b, and 689 c)correspondingly. Assembling device 661, assembling a content stored inthe array, can select the servers from which to retrieve regardless ofits Internet backbone operator connection, and in a manner that combineserasure-coded fragments coming from different Internet backboneoperators.

In a second example, assembling device 661 can select the serversregardless of the hosting ISP, and in a manner that combines fragmentsfrom several ISPs.

In a third example, servers 697 a and 697 b are owned by a privatecorporate 689 a, server 697 c is hosted by an ISP 689 b and servers697(N−1) and 697(N) are connected to the Internet 300 via an Internetbackbone operator. Assembling device 661 can select the serversregardless of the hosting entity, and in a manner that combinesfragments from servers hosted in private corporate, ISP and backboneoperators.

Still referring to FIG. 36, in one example servers 697 a and 697 b,server 697 c, and servers 697(N−1) and 697(N) are connected to theInternet 300 via first, second, and third hosting providers (689 a, 689b, and 689 c) correspondingly. Assembling device 661 can select theservers regardless of the hosting provider, and in a manner thatcombines erasure-coded fragments from several hosting providers. At anypoint in time, the operator of the distributed storage system canperform a cost effectiveness analysis of the hosting and data transportservices provided by each hosting provider, and look for new hostingproviders as candidates for replacement of one or more of the currenthosting providers. If such a replacement is found, such as when a betterhosting deal can be obtained, the distributed storage operator canterminate the services of such hosting provider(s), and replace it witha better deal.

In one example, if the second hosting provider 689 b is found to be tooexpensive, it can be replaced with a fourth provider (not illustrated),while the first and third providers are still maintained, and provideservice to the distributed storage system via remaining servers 697 a,697 b, 697(N−1) and 697N. Server 697 c will be terminated, andoptionally replaced by other servers belonging to the fourth hostingprovider. Optionally, the entire process is performed without affectingthe streaming to the assembling device 661, or any other client groups,and no inter-server cooperation may be necessary throughout the processof replacing the hosting provider.

FIG. 37 illustrates one embodiment in which different data centers 1461to 1464 host fractional-storage servers. The servers store erasure-codedfragments encoded with a redundancy factor R greater than one. Aplurality of assembling devices 1499 obtain fragments needed forstreaming contents. No group of servers within any one of the datacenters store more than (1−1/R) of the fragments associated with asingle segment to be reconstructed; meaning that if any one of the datacenters stop delivering fragments, the other data centers still compriseenough erasure-coded fragments needed to decode the fragments. Upontermination of a fragment delivery service from any one of the datacenters, the servers of the data center whose fragment delivery servicewas terminated are deselected for fragment delivery, and other serversin other data centers are selected for fragment delivery instead, whilethe streaming of the contents to affected assembling devices continuesduring this short deselection-reselection process, and withoutdisrupting any ongoing streaming operation. Usually, each data centerhosts more than one server, but a data center may also host a singleserver. In one embodiment, more than 200 servers are hosted in more than20 data centers. In one embodiment, more than 10,000 servers are hostedin more than 100 data centers, and deliver fragments at an aggregatedthroughput of more than 10 Tera-bit per second.

In one embodiment, different data centers feature significantlydifferent characteristics. Examples of different characteristics include(i) available storage space, (ii) available fragment deliverythroughput, (iii) latency in response to fragment requests, (iv) adifference in the tier or size of the network to which the data centeris directly connected, (v) ownership of the data center, (vi) operationcost, (vii) data center outage periods and frequency, (viii) data centerreliability, and/or (ix) the nature or capacity of the line connectingthe data center to the Internet.

In one embodiment, some of the data centers may belong to one or more ofthe following entities: a hosting provider, a backbone or Tier-1 networkoperator, and/or a corporation.

In one embodiment, the data center is any structure connected to theInternet, and providing an Internet connection to at least one housedfractional-storage server. In one embodiment, the data center isconnected with a fixed bandwidth link to the Internet. In oneembodiment, the data center is connected to a router that is a part ofan Internet backbone or Tier-1 network.

In one embodiment, the assembling devices 1499 use a fragment pullprotocol to retrieve fragments from the servers and to approach newservers, optionally on-the-fly while streaming contents, instead ofservers whose data center's fragment-delivery service was terminated.

In one embodiment, the assembling devices 1499 use a push protocol toobtain fragments from the servers by utilizing multiplesub-transmissions. Servers whose data center's fragment-delivery servicewas terminated are replaced, optionally on-the-fly while streamingcontents, by other servers which operate as the sub-transmissionsources.

In one example, the deselection-reselection process takes a few secondsor less. In one example, the deselection-reselection process is donefaster than it takes to play the content stored in one relatively shortsegment. In one example, the deselection-reselection process is done byassembling devices. In one embodiment, the reselection of servers isdone by a control server.

In one embodiment, termination of fragment delivery service from any oneof the data centers may be a result of the data center underperformingin comparison to other data centers. The termination in this case isusually triggered by the fragment-delivery service operator. Examples ofunderperformance include (i) the cost of delivering data being higherthan delivering data from other centers, (ii) the transmitted fragmentsbeing subject to higher fragment loss rate as compared to other centers,(iii) the transmitted fragments being subject to higher latency orlatency variance as compared to other centers, and/or (iv) the outageperiods being longer or more frequent than those of other centers.

In one embodiment, termination of fragment delivery service from any oneof the data centers may be a result of the data center operator orhosting provider not wanting to continue hosting the fractional-storageservers. Such termination may be abrupt and without a warning.

In one embodiment, just before service termination, the aggregatedunutilized fragment-delivery bandwidth available to the alternativeservers is larger than the fragment delivery throughput via the datacenter whose service is terminated. In other words, there is enoughbandwidth among the remaining servers to support the streamingthroughput of the system prior to the termination event.

In one embodiment, just before service termination, the terminatedservice is still capable of delivering a substantial fragment throughputbut is underperforming in comparison to the other data centers. In otherwords, the center is still able to perform prior to service termination.

In one embodiment, servers housed in data centers whose fragmentdelivery service is about to be terminated, are excluded from the poolof servers considered by assembling devoices or control servers as validsources of fragments. The service is then terminated after approximatelyall assembling devices have stopped using these servers as fragmentsources.

In one embodiment, a new data center housing servers storing uniquefragments is added to the service before the step of terminating thefragment delivery service of a certain center. In this case, theaggregated unutilized fragment delivery bandwidth of the new data centerand the remaining data centers is larger than the fragment deliverythroughput supplied by the service to be terminated.

In one embodiment, from time to time and on a regular basis, the systemadds and excludes data centers from the streaming operations, whilemaintaining continuous streaming. In one embodiment, data centers thatunderperform compared to the other data centers are candidates forexclusion. In one embodiment, most of the excluded data centers providedfragments to approximately the smallest number of assembling devicesover a predefined period before their exclusion.

In one embodiment, the erasure-coding used is a rateless-coding,enabling practically an infinite number of unique fragments. Therefore,it is possible to assign unique fragments to servers of newly added datacenters, regardless of how many data centers are added and removed, andat what frequency. New and unique fragments can always be calculated andused. In one embodiment, the fragments stored on servers of the excludeddata center are usually not stored again on servers of the remaining orto be added data centers, especially when using rateless coding.

In one embodiment, over a long period, there are more additions of datacenters than exclusions, and therefore the streaming and storagecapacity of the streaming system increases.

Still referring to FIG. 37, the following example illustrates some ofthe above principles: data centers 1461 to 1464 transmit fragments viacommunication links 1471 to 1474 at throughputs of 1451 to 1454respectively to assembling devices 1499 over the Internet 1430. Theredundancy factor of the fragments is, as an example, 2; meaning thatapproximately ½ of any of the stored fragments can be used to decode thefragments. In this example, the servers in each of the centers store ¼of the fragments. After evaluating the performance of the differentcenters, a conclusion is made that center 1462 is underperformingrelative to the other centers. A decision is then made to terminatefragment delivery service from center 1462, and the service isterminated. Termination can be done by removing the fragment deliveringservers from the center, by removing the fragment delivery applicationfrom servers belonging to the data center, or by any other applicablemanner. Referring now to FIG. 37 and FIG. 38, at the point oftermination, fragment throughput 1452 from center 1462 is reduced to1452′, which is zero. The lost throughput must be gained in order toavoid disruption of fragment delivery to some of the assembling devices.The lost throughput is gained by diverting fragment traffic from center1462 to the other centers. The diversion can be made using a fragmentpull protocol or using sub-transmissions in accordance with someembodiments. After the diversion, fragment throughputs 1451, 1453, and1454 increase to 1451′, 1453′, and 1454′ respectively, such that thethroughput difference: (1451′+1453′+1454′)−(1451+1452+1453+1454) equalto or greater than zero. It is noted that since center 1462 stored only¼ of the fragments, the remaining ¾ of fragments are still enough tosupport fragment decoding, since the redundancy prior to the terminationevent was 2, and has now dropped to (¾)/(½)=1.5. In other words, thetermination satisfies the requirement that the terminated center storesno more than (1−1/R) of the fragments. And indeed, ¼<(1−1/R), wherein(1−1/R)=(1−½)=½ in this example. The example continues in FIG. 39,wherein a new data center 1465 joins the system by hosting fragmentdelivering servers. The new center delivers a throughput of 1455, whichis added to the other throughputs of the other remaining centers.Optionally, the fragments stored in the servers housed in data center1465 are different from the fragments previously stored on servershoused in data center 1462. Optionally, the different fragments arederived using a rateless code, which assured that there wouldpractically never be a shortage of new unique fragments.

In the claims, a sentence such as “erasure-coded fragments encoded witha redundancy factor R>1 and associated with segments of streamingcontents” is to be interpreted as erasure-coded fragments encoded withone redundancy factor or with a plurality of redundancy factors greaterthan one. For example, some fragments associated with a first set ofsegments of content may have a redundancy factor of two, and somefragments associated with a second set of segments of the same contentmay have a redundancy factor of three.

FIG. 40 illustrates one embodiment in which fractional-storage serverswithin data centers 3661 to 3664 store erasure-coded fragments encodedwith a redundancy factor greater than one. A plurality of assemblingdevices 3699 obtain decodable sets of fragments from subsets of theservers and measure fragment delivery parameters that are indicative ofdelivery performances, such as latency in responding to requests, orfragment loss ratios. Each assembling device can readily make themeasurements on fragments sent to it. Decisions are constantly made bythe assembling devices, a control server, or any other decisioncomponent, regarding selection and reselection of servers participatingin the subsets. The decisions are based on the measured parameters, andare made in order to improve the measured parameters. After many suchdecisions are made for or by many assembling devices, it is possible toestimate the performances of the different data centers. A data centerthat is underperforming relative to other data centers is likely tofeature one or more of the following: (i) delivers fewer fragments toassembling devices as compared to other data centers, (ii) incurs highercost per fragment delivery, and thus is less cost effective compared toother data centers, (iii) utilizes a lower percentage of the fragmentdelivery bandwidth available to it, as compared to other centers, and/or(iv) exhibits any other measurable degradation in performance level,that is a result of server participation in subsets, and that can beused to differentiate it over well performing data centers. Thepreference of the assembling devices, or other decision component, forsome servers over other servers creates a “natural selection” processthat can be utilized to distinguish well performing data centers overunderperforming data centers. After the data centers are distinguished,decisions can be made regarding a future utilization of each center.

In one embodiment, one or more of the following is used as the measuredfragment delivery parameters: latency in responding to data requests,variance in latency in responding to fragment requests, fragment loss,service outage, and/or reported load level encountered by the serverswhen delivering fragments. In one embodiment, the assembling devices areconfigured to obtain the fragments using a fragment pull protocol thatis used for estimating at least one of the parameters.

An underperforming data center is likely to include servers that areless frequently selected for participation in subsets than serversbelonging to other well performing data centers. This, in turn, reducesthe fragment delivery throughput from the underperforming center, ascompared to other centers. In one embodiment, centers having lowerdelivery throughputs over time are excluded from the system.

In one embodiment, an underperforming data center has a higher cost ofdelivering a fragment than other centers. A center that includes serversthat are less frequently selected for participation in subsets, comparedto servers belonging to other well performing data centers, will havelower fragment delivery throughput as compared to other centers.Assuming that the fragment delivery operator is paying a fixed price forthat center's delivery services, the result is a decrease in fragmentdelivery cost efficiency. In this case, one option is to exclude theunderperforming center from the system, and to stop delivering fragmentsfrom it. Another option is to reduce the amount of bandwidth acquiredfrom that center, to a level that is more appropriate to actualthroughputs, or to downscale the service agreement and reduce the fixedprice. This may increase the cost efficiency of the center back to anacceptable level. If further reduction in throughputs are observed, andcost efficiency falls again, then the process of reducing the acquiredbandwidth or downscaling the service agreement can be repeated, untilpossibly eliminating the center as a fragment source.

In one embodiment, an underperforming data center has a percentage ofutilized fragment delivery bandwidth out of available fragment deliverycapacity that is lower than other better performing centers. In thiscase, one option is to exclude the underperforming center from thesystem, and stop delivering fragments from there. Another option is toreduce the amount of available fragment delivery capacity from thatcenter, to a level that is more appropriate to actual throughputs. Thismay decrease the percentage of utilized fragment delivery bandwidth outof available fragment delivery capacity of the center back to anacceptable level. If further reduction in throughputs is observed, thenthe process of reduction in available fragment delivery capacity can berepeated, until possibly eliminating the center as a fragment source.

In one embodiment, after identifying an underperforming data center, oneor more of the following actions may be taken: (i) excluding the datacenter from the system, with fragments no longer being delivered fromthere; (ii) reducing the amount of bandwidth acquired from the datacenter. If the center is still underperforming, then the process ofacquired bandwidth reduction can be repeated, until possibly eliminatingthe center as a fragment source. and/or (iii) downscaling the servicelevel agreement. If the center is still underperforming, then theprocess of downscaling can be repeated, until possibly eliminating thecenter as a fragment source.

In one embodiment, a decision component determines which servers are totransmit fragments to which assembling device, and occasionally changesat least some of the servers of the subsets. Optionally, the decisioncomponent is implemented at each assembling device. Alternatively, thedecision component is implemented at a control server, which may receivethe measured fragment delivery parameters from the assembling devices.

In some embodiments, one or more of the following embodiments may beused for enhancing the capacity of one or more data centers. In oneembodiment, a data center exhibiting high fragment delivery throughput,which approaches the available fragment delivery capacity of the center,is a candidate for capacity enhancement. In this case, additionalfragment delivery bandwidth can be acquired from the center, oralternatively, the service level agreement can be upgraded, such thatthe percentage of utilized fragment delivery bandwidth out of availablefragment delivery capacity decreases. If, over time, the data centeragain exhibits a level of fragment delivery throughput approaching theavailable fragment delivery capacity, the process of capacityenhancement may be repeated. In one embodiment, a data center exhibitinghigh fragment delivery cost efficiency is a candidate for capacityenhancement. In this case, additional fragment delivery bandwidth may beacquired from the center, or alternatively, the service level agreementcan be upgraded. If, over time, the data center still exhibits highfragment delivery cost efficiency, the process of capacity enhancementcan be repeated, until a reduction in cost efficiency is identified. Thecost efficiency may be measured in absolute terms, or may be measuredrelative to other data centers. In one embodiment, at least one of thedata centers is connected to the Internet via a high bandwidth fixedline having a certain fragment delivery capacity, and when the fragmentdelivery throughput from that center approaches the capacity of thefixed line, the capacity is upgraded. In one embodiment, at least one ofthe data centers provides Internet bandwidth services to multipleapplications via a shared communication line, the fragment deliverythroughput in that center is limited to a capacity smaller than thebandwidth capacity of the shared line, and when the fragment deliverythroughput from the center approaches the limited capacity, the limitedcapacity is enhanced. The capacity may optionally be enhanced byupgrading the service agreement with the data center. In one embodiment,at least one of the data centers is connected to the Internet via a highbandwidth fixed line having a certain fragment delivery capacity, andwhen the fragment delivery throughput from that center approaches thecapacity of the fixed line, the capacity may be upgraded. In oneembodiment, the quality of the fragment delivery from at least one ofthe data centers is monitored, and when the fragment delivery throughputapproaches a level that lowers the quality, the bandwidth capacity ofthe center is enhanced in order to improve the quality. In oneembodiment, when the fragment delivery throughput of a data centerapproaches its fragment delivery capacity, at least one other datacenter located nearby is added to the system.

In one embodiment, the system comprises multiple data centers. Thefragment delivery performances of the centers are monitored, optionallyover a long period, in order to enable the exclusion of mostunderperforming data centers even if still capable of providing asubstantial fragment delivery throughput.

FIG. 40 and FIG. 41 illustrate some of the above principles andembodiments, in accordance with one example. Data centers 3661 to 3664include fractional-storage servers. Multiple assembling devices 3699obtain erasure-coded fragments from the servers. At first, the fragmentdelivery throughputs 3651 to 3654 delivered by data centers 3661 to 3664over communications lines 3671 to 3674 respectively, are approximatelyequal to each other. Over time, the assembling devices measurefragment-delivery parameters associated with servers of the differentcenters, and select subsets of servers from which to obtain decodablesets of fragments accordingly. The measured parameters associated withcenter's 3661 servers are not as good as the parameters measured fromother servers. Center's 3661 servers are therefore less frequentlyselected by assembling devices 3699, and the result is a reduction infragment delivery throughput from that center from 3651 to 3651′. At thesame time, the measured parameters associated with center's 3664 serversare better than parameters measured by assembling devices from otherservers. Center's 3664 servers are therefore more frequently selected byassembling devices, and the result is an increase in fragment deliverythroughput from that center from 3654 to 3654′. The performance of thedifferent data centers can now be compared, and decisions can be maderegarding the future utilization of the center's resources. Thefollowing two examples illustrate performance comparisons andcorresponding decisions.

In the first example, data center 3661 is underperforming in a sensethat it has a lower percentage of utilized fragment delivery bandwidthout of available fragment delivery capacity as compared to the otherbetter performing centers. In the second example, data center 3661 isunderperforming in a sense that it has a lower fragment deliverycost-efficiency as compared to the other better performing centers. Inboth cases, fragment delivery service from center 3661 may beterminated, or reduced by acquiring less bandwidth from center 3661 orby downgrading the service level agreement with the center. On the otherhand, data center 3664 is performing well, in a sense that it has ahigher percentage of utilized fragment delivery bandwidth out ofavailable fragment delivery capacity as compared to the other betterperforming centers, or alternatively a good fragment deliverycost-efficiency. Therefore, the fragment delivery service levelagreement with data center 3664 may be upgraded, or additional fragmentdelivery bandwidth may be acquired.

FIG. 42 illustrates one embodiment of a fractional-storage systemstoring erasure-coded fragments. Content 100, which may optionally bestreaming content, is segmented into content segments 101 a, 101 b to101 j (for brevity referred to as segments). Each of the segments isencoded into erasure-coded fragments. For example, segment 101 a isencoded into erasure-coded fragments 390 a to 390(N). The erasure-codedfragments are distributed to the fractional-storage servers 399 a to399(N) and/or to the bandwidth amplification devices 610 aa. Theerasure-coded fragments are then obtained by assembling devices like 661or proxy servers like proxy server 661 s from the fractional-storageservers 399 a to 399(N) and/or the bandwidth amplification devices 610aa. The obtained erasure-coded fragments are decoded to reconstruct thesegments. The proxy server 661 s may broadcast/multicast and/orre-stream the reconstructed content, optionally using standard streamingtechnique, to its client(s) 661 o, optionally over network 300 n. Insome embodiments, the content distribution is performed in real time. Insome embodiments, the content assembly is performed in real time and thepresentation starts a short time after the content request.

Similarly to content 100, additional contents are segmented, encodedinto erasure-coded fragments, and distributed to the fractional-storageservers and/or to the bandwidth amplification devices. Each segment maybe reconstructed independently of other segments by obtaining anddecoding enough erasure-coded fragments generated from that segment.

In some embodiments, the encoding scheme is erasure codes and/orrateless codes. In some embodiments, the fractional-storage servers 399a to 399(N) are Content Delivery Network (CDN) servers, optionallyaccessed over the public Internet. In some embodiments, the control,management, content reception, content segmentation, segment encoding,erasure-coded fragment distribution, allocation of bandwidthamplification devices, and/or other kind of central supervision andoperation may be performed by managing server(s) 393, which may be apart of the CDN network. It is noted that the term “fractional-storageserver” is not limited to a large server and, according to the context,may include a fractional-storage bandwidth amplification device, afractional-storage peer server, or other types of fractional-storageservers.

In one embodiment, device 661 o is a non-assembling CPE, such as a STB,PC or gaming console, capable of performing standard request, reception,and decoding of video over IP network. In one embodiment, server 661s—also referred to as proxy server, assembling server, and in some casesassembling device—performs three primary functions: (i) receipt ofcontent requests from non-assembling client device 661 o; (ii) assemblyof content, as requested by client 661 o, from the fractional-storageservers and optionally from the bandwidth amplification devices; (iii)optionally, conversion of the assembled content into a streaming format;and (iv) transmission of the streaming content to the requesting client661 o. Client 661 o can then store the content, or present it. In oneembodiment, the assembled content is a general web content, includingHTML, FLASH or any other data format that can be found in a web-basedsite.

In one embodiment, although server 661 s is illustrated as beingconnected to network 300 on one side and to network 300 n on the other,server 661 s may also be connected to another network element, such as arouter, which makes the topological connection between networks 300 and300 n. In that case, server 661 s communicates with both networks 300and 300 n via the other network element.

FIG. 43 illustrates one embodiment of assembling content utilizing aproxy server. The client 661 o requests a specific content from server661 s (both illustrated in FIG. 42). Server 661 s then initiates a realtime process of obtaining erasure-coded fragments 720 a to 720(K) attime T1 and subsequent erasure-coded fragments 730 a to 730(K) at timeT2. Server 661 s then decodes the erasure-coded fragments into segments710 a, 710 b at time T2 b and T4. The segments are then integrated intothe original requested content 763 at time T5. Optionally, theintegrated content 763 is made available to the next processes in realtime, such that it aggregates segments at an average rate no lower thanthe rate of segment presentation, in order to keep the entire process inreal time. Meaning that since T5, the content is available forcontinuous on-the-fly presentation, up to the end of the content beingassembled. In one embodiment, fragments 720 a to 720(K) and 730 a to730(K) are retrieved using a fragment pull protocol. In anotherembodiment, fragments 720 a to 720(K) and 730 a to 730(K) are obtainedusing a push protocol, wherein multiple sub-transmissions may be used todeliver the fragment sequences to server 661 s.

Optionally, at time T7, server 661 s starts a process 764 of transcodingcontent 763, optionally into a suitable format supported by the client661 o, and then encapsulating the result into a streaming format to bedelivered to client 661 o. This is done in real time, such that sinceT7, the content is ready to be streamed continuously up to the end ofthe content. Then, at time T8, content 764 is streamed 765 to client 661o.

In one embodiment, server 661 s is co-located with a Broadband RemoteAccess Server (BRAS). In one embodiment, server 661 s is located in aCentral Office (“CO”) or in an Internet Exchange Point (“IX/IXP”). Inone embodiment, server 661 s is: one of servers 399 a to 399(N), all orsome of servers 399 a to 399(N) operating in the mode of server 661 s,an IP aggregation network, a last mile network, part of network 300,and/or a private network. In one embodiment, network 300 n is an ISPnetwork. In one embodiment, network 300 belongs to one Internet backboneprovider, and network 300 n belongs to a second Internet backboneprovider. In one embodiment, some or all of clients 610 aa are connectedto network 300 n, and not to network 300. In one embodiment, client 661o requests and controls content interaction with server 661 s usingstandard RTCP. In one embodiment, server 661 s streams 765 content 764to client 661 o using standard RTP/RTSP. In one embodiment, server 661 sprogressively downloads 765 content 764 to client 661 o using FLASH overTCP/IP.

In one embodiment, a CDN is created by the aggregated bandwidth andstorage capacity of the participating erasure-coded fractional-storageservers. In one example, a large scale CDN includes several hundreds orthousands of fractional-storage servers connected to the Internet. Theseservers send erasure-coded fragments to a large number, potentiallymillions, of assembling devices. In order to keep costs low for sendinga large number of fragments from fractional-storage servers toassembling devices, the servers are located on the Internet backbone, orclose to it.

The current Internet backbone primarily comprises different Tier one ISP(or other) networks that interconnect at various Internet ExchangePoints (IX or IXP), using peering agreements. Tier one ISPs, or otherbackbone-forming network entities, can reach any portion of the Internetvia other Tier one ISPs or other backbone-forming networks, withoutpaying any Internet transit fee, and solely by utilizing mutual peeringagreements. In order to gain access to large amounts of inexpensivebandwidth, the fractional-storage servers are typically located on theInternet backbone. This means that the servers are either co-located(and connected) with a core switching router that interconnects theInternet backbone networks at an IXP, or, alternatively, co-located (andconnected) with a router which is part of the backbone network,typically located at a data center or co-location center.Fractional-storage servers can also be located close to the Internetbackbone, which means that they are co-located (and connected) with arouter which is part of a Tier two ISP network, which has a highbandwidth connection with at least one Tier one operator, to which itpays transit fees in order to potentially reach all portions of theInternet. FIG. 44 illustrates one example of a fractional-storage server3001, which is one of a plurality of servers forming a large-scale CDN,located on the Internet backbone by being connected to the Internetbackbone via IXP 3091. In a second example, fractional-storage server3002 is located on the Internet backbone by being connected to a Tierone backbone network 3080. In a third example, fractional-storage server3011 is located close to the Internet backbone by being connected to aTier two ISP network 3070, which is connected to the backbone via Tierone ISP network 3081. In one embodiment, a typical fractional-storageserver is located on the backbone or close to the backbone by beingattached to a switching router via a high bandwidth port, such as a 1Gbps, 10 Gbps, or a higher bandwidth port, such as high-speed Ethernetport, usually carried over a fiber, or suitable short-distance copperlines. In one embodiment, in a typical deployment using high bandwidthconnections (in 2009 terms), each of about 1,000 fractional-storageservers is located on the backbone or close to the backbone and isconnected to the backbone via a dedicated (guaranteed bandwidth) 1 GbpsEthernet port, resulting in an aggregated throughput of 1,000 Gbps,which can serve about one million subscribers of standard definitionstreaming video, such as client device 3020, simultaneously. Suchaggregated bandwidths would have required a substantially larger numberof fractional-storage servers, had they been connected to otherlocations in the Internet, such as at edges of the Internet (close tolast mile networks), Tier 3 ISPs, or at the user premises. Moreover, insome embodiments, the cost of streaming the mentioned 1,000 Gbps whenthe fractional-storage servers are located on the Internet backbone, orclose to the Internet backbone, is expected to be significantly lowerthan what is expected when the servers are located elsewhere asmentioned before.

FIG. 45 illustrates one example where an assembling server 4020 islocated at the juncture 4010 between two networks: the first network isan ISP transit network 4014 that connects the juncture to the Internetand provides Internet transit via a switching router 4015, and thesecond is a last mile network 4041 that connects end users 4051 to theInternet via a switch 4031 (located, for example, inside a CentralOffice, a Head-End, or a street-level cabinet). In one embodiment, thejuncture 4010 is a network operated by a local ISP that pays transitfees for Internet traffic passing through the transit network 4014, andlast mile fees for traffic passing through the last mile network 4041. Aunique property of the juncture 4010 is that it is possible for anassembling server 4020 located at the juncture to receive erasure-codedfragments sent by fractional-storage servers, such as 4001 and 4002, toassemble content, and to stream the content to a client 4051 via thelast mile network 4041, without incurring any additional costs incomparison to other scenarios, such as where Internet packets flow fromthe Internet backbone to a Tier two ISP network to the Internet backboneand to the last mile network. In other words, since the assemblingserver 4020 is located at the juncture, it does not create any extratraffic via networks 4014 and 4041. The assembling server can also belocated at or close to an edge of the Internet, which may include thejuncture, or a point above server 4015, such as at the transit network4014 connecting the juncture to the Internet. When located at or closeto an edge of the Internet, the assembling server has the potential notto incur additional transit fees as a result of the relaying operation,since approximately the same traffic would have to pass via the sametransit network in a normal scenario. Another beneficial location forthe assembling server is at the home premises, since, clearly, arelaying operation performed there does not add any significant trafficto higher levels of the network. In contrast to the above-suggestedlocations, in some cases an assembling server may be located at anarbitrary point on the backbone, or at other high-level points of theInternet, where it incurs additional transit fees, as fragmentsassembled by the server flow once over an Internet transit network goingfrom a fractional-storage server to the assembling server, and then asecond time when streamed by the assembling server to a destinationclient over an Internet transit network.

In one embodiment, an assembling server communicates with a plurality offractional-storage servers via the Internet on one hand, and with aclient device on the other hand. The fractional-storage servers storeerasure-coded fragments associated with several contents, such that eachcontent can be completely reconstructed by assembling enough fragments.The assembling server may quickly reconstruct one of the contents, suchthat from the time it is knows which content to reconstruct, it takesthe assembling server no more than several seconds to retrieve enoughfragments and reconstruct the specific content. In one example, theassembling server is connected to the Internet via a guaranteed 10 Gbpsline, such that it can completely retrieve a 1 GByte standard-definitionmovie file in approximately 1 [GByte]×8 [bits per byte]/10[Gbps]=0.8seconds, plus at most 0.3 seconds communication latency=1.2 seconds. Inthis example, the assembling server communicates approximately inparallel with 1,000 fractional-storage servers (out of a possibleseveral thousands), possibly using a pull protocol or using a pushprotocol (optionally implemented by multiple sub-transmissions), suchthat each of the selected 1,000 servers sends a unique 1 MByteserasure-coded fragment to the assembling server. The entirereconstructed content occupies one segment, and the fractional-storageserver needs to send only one erasure-coded fragment to the assemblingserver. Other configurations in which the content is segmented intomultiple segments, and/or in which the 1 MBytes erasure-coded fragmentincludes many fragments are also possible. After quickly reconstructingthe content, the assembling server may stream the 1 GByte content to arequesting client having approximately a 1 Mbps download link over aperiod of two hours. In the described embodiment, the assembling serverquickly obtains a large file stored as multiple erasure-coded fragmentsover multiple fractional-storage servers, and, potentially, slowlytransmits the reconstructed file to a client via a much slowerconnection than the connection used for assembling the content. In oneembodiment, the client requests a file from the assembling server, theassembling server quickly obtains the requested file fromfractional-storage servers, and briefly following the client's request(optionally a matter of seconds), starts streaming the newly obtainedfile to the requesting client. It is noted that the assembling serverneed not store the requested file internally, as it can quickly fetch it(or part/s of it) when needed. In the above example, the 1,000fractional-storage servers share the bandwidth load of providing therequested file, such that each fractional-server sends a fragment, orseveral fragments, to the assembling server at a rate of approximately10[Gbps]/1,000 [servers]=10 Mbps. The fractional-storage servers, asmentioned in the last example, may serve multiple assembling servers inparallel, each requiring a 10 Mbps bandwidth. In one example, thefractional-storage servers are fractional-storage CDN servers locatedclose to or on the Internet backbone, each servicing dozens ofassembling servers in parallel. The placement of the CDN servers closeto or on the Internet backbone provides low cost and high bandwidthInternet transit.

By using a pull protocol or a push protocol with multiplesub-transmissions, the assembling device can obtain erasure-codedfragments from one, two or more different arrays of CDN servers and/orbandwidth amplification devices seamlessly.

FIG. 46 illustrates one embodiment in which fractional-storage servers399 a and 399 b are part of a server array. Fractional-storage servers399 a and 399 b store erasure-coded fragments 310 a and 310 b of a firstcontent, and erasure-coded fragments 320 a and 320 b of a secondcontent. Server 393 is a control server that manages a pool of twelveregistered bandwidth amplification devices surrounded by ellipse 599.One or more of the twelve bandwidth amplification devices may beassigned to one or more of the fractional-storage servers participatingin the array. In the initial stage, no assignments have been made, andthe twelve bandwidth amplification devices in pool 599 are ready toreceive instructions. Next, the control server 393 allocates sixbandwidth amplification devices of group 610 aa to server 399 a, and sixbandwidth amplification devices of group 610 bb to server 399 b.Registering the bandwidth amplification devices with the servers may beprocessed using any appropriate method. From groups 610 aa and 610 bb,three bandwidth amplification devices 610 a and 610 b are allocated tostore erasure-coded fragments 310 a and 310 b respectively (and,optionally, other erasure-coded fragments associated with consequentsegments of the content); and three bandwidth amplification devices 620a and 620 b are allocated to store erasure-coded fragments 320 a and 320b respectively (and, optionally, other erasure-coded fragmentsassociated with consequent segments of the content). After theseallocations have been made, fractional-storage server 399 a forwardserasure-coded fragment 310 a to group 610 a, and erasure-coded fragment320 a to group 620 a. Fractional-storage server 399 b forwardserasure-coded fragment 310 b to group 610 b, and erasure-coded fragment320 b to group 620 b. At the end of the allocation and forwardingprocess, the bandwidth amplification devices are ready to act asbandwidth amplifiers to the fractional-storage server array 399 a and399 b. Optionally, the allocation of bandwidth amplification devices tospecific contents is performed by either the control server 393, or eachfractional-storage server 399 a and 399 b.

It is noted that each bandwidth amplification device is not restrictedto storing and serving erasure-coded fragments associated with a singlecontent, and it is possible for each bandwidth amplification device tostore and serve multiple erasure-coded fragments associated withmultiple contents. The tradeoff in this case is that the moreerasure-coded fragments from more contents are stored and served, thelower the bandwidth amplification factor, since the rate of forwardingfragments from the server to the bandwidth amplification devicesincreases, while the outgoing bandwidth available for each bandwidthamplification device remains the same.

In one embodiment, when a CDN server receives a request for anerasure-coded fragment, it may supply the erasure-coded fragment orsupply an address of a bandwidth amplification device having an image ofthe requested erasure-coded fragment. Optionally, a bandwidthamplification device storing one erasure-coded fragment of a specificcontent also stores an image of some or all other erasure-codedfragments associated with the specific content (which are stored on thespecific CDN server). Alternatively, the bandwidth amplification devicestores unique erasure-coded fragments generated from the same segmentsused for generating the erasure-coded fragments stored on the specificCDN server. In these cases, the assembling device may approach thebandwidth amplification devices instead of the CDN server for therelevant erasure-coded fragments of the specific content until (i) theend of the content; (ii) a predefined time period elapses; (iii)receiving an appropriate message; or (iv) a combination of theaforementioned.

In one embodiment, an assembling device tries to obtain an erasure-codedfragment or sub-transmission from the relevant server, and if the serverdoes not have the necessary bandwidth to respond with fragment/s, theserver relays the fragment request/s to relevant bandwidth amplificationdevices. The relevant bandwidth amplification devices can then send thefragment/s directly to the assembling device.

In one embodiment, unique erasure-coded fragments can be distributedbetween two types of devices: (i) high bandwidth fractional-storageservers, such as CDN servers, and (ii) relatively low bandwidth andstorage devices acting as bandwidth amplification devices, such aspeer-to-peer (P2P) devices. Since the fragments distributed between thetwo types of devices are unique, any combination of devices, from bothtypes, can be used to obtain a decodable set of fragments, if thecombination of devices stores a decodable set of fragments. In oneembodiment, there are at least ten times more bandwidth amplificationdevices than high bandwidth servers, and the redundancy factor used indecoding the fragments is greater than 10. In this case, the servers canbe used all or most of the time, and the bandwidth amplification devicescan be used from time to time, according to bandwidth requirements, andaccording to the availability of the bandwidth amplification devices. Inone embodiment, the processes of obtaining a fragment from a server andfrom a bandwidth amplification device are essentially the same, and thefragments are essentially identical in construction and format. In oneembodiment, the high redundancy factor needed to support a large hybridarray of servers and bandwidth amplification devices is achieved usingrateless coding techniques.

FIG. 47 illustrates one embodiment of hybrid Servers-P2P system using Nunique erasure-coded fragments 550 to 559, generated from the samesegment belonging to content. The fragments are partitioned into twogroups: server group comprising fragments 550 to 552; and P2P group,comprising fragments 553 to 559. Fragments belonging to the first group(550 to 552) are distributed among fractional-storage servers 560 to 562respectively. Fragments belonging to the second group (553 to 559) aredistributed among P2P devices (acting as bandwidth amplificationdevices) 563 to 569 respectively. In one example, N=30,003, and thereare close to 30,000 P2P devices. The following reconstruction modesassume that any three fragments are sufficient to reconstruct a segment:

In one reconstruction mode, the servers 560 to 562 have an aggregatedfragment-delivery bandwidth sufficient to supply all fragment demands ofassembling devices. In this case, the assembling devices obtainfragments only from the servers, and do not obtain any fragments fromP2P devices.

In another reconstruction mode, the servers 560 to 562 have anaggregated fragment-delivery bandwidth that is insufficient to supplyall fragment demands of assembling devices. In this case, the assemblingdevices obtain fragments from both the servers and the P2P devices. Anycombination of three fragments forms a decodable set of fragments.Selecting combinations for the different assembling devices, accordingto bandwidth availability of both servers and P2P devices, results in afragment delivery bandwidth that may approach the aggregated bandwidthof both the servers and P2P devices. According to the N=30,003 example,each P2P device has a fragment delivery bandwidth of 100 Kbps, and eachserver has a fragment delivery bandwidth of 1 Gbps. The three servers560 to 562 contribute 1 Gbps×3=3 Gbps of fragment throughput. The 30,000P2P devices contribute 100 Kbps×˜30,000=˜3 Gbps. The total fragmentdelivery bandwidth of the hybrid system therefore approximately equals 3Gbps+3 Gbps=6 Gbps. A Hybrid system comprising such a large number ofP2P devices needs a large redundancy factor. In the above example, theredundancy factor needed is approximately 30,003/3=10,000. Such largefactors can be realized using rateless codes. In the above example, thebandwidth amplification factor=the total possible bandwidth includingboth servers and P2P devices divided by the maximal possible bandwidthusing only the servers=6 Gbps/3 Gbps=2.

In one example, 1,000 fractional-storage CDN servers, each having afragment delivery bandwidth of 10 Gbps, are combined with 10 million P2Pdevices, each having a fragment delivery bandwidth of 1 Mbps, to producea (1,000×10G)+(10M×1M)=20 Tbps streaming system.

In the claims, a sentence such as “the erasure-coded fragments supportsource-selection diversity” is to be interpreted as fragments encodedusing any kind of erasure-code that can produce N unique fragments, fromwhich C combinations of decodable sets of fragments can be selected,wherein C is much greater than N. Standard parity checks, standardchecksums, and standard cyclic redundancy checks (CRC) are examples ofcodes that do not support source-selection diversity.

In this description, numerous specific details are set forth. However,the embodiments of the invention may be practiced without some of thesespecific details. In other instances, well-known hardware, software,materials, structures and techniques have not been shown in detail inorder not to obscure the understanding of this description. In thisdescription, references to “one embodiment” mean that the feature beingreferred to may be included in at least one embodiment of the invention.Moreover, separate references to “one embodiment” or “some embodiments”in this description do not necessarily refer to the same embodiment.Illustrated embodiments are not mutually exclusive, unless so stated andexcept as will be readily apparent to those of ordinary skill in theart. Thus, the invention may include any variety of combinations and/orintegrations of the features of the embodiments described herein.

Although some embodiments may depict serial operations, the embodimentsmay perform certain operations in parallel and/or in different ordersfrom those depicted. Moreover, the use of repeated reference numeralsand/or letters in the text and/or drawings is for the purpose ofsimplicity and clarity and does not in itself dictate a relationshipbetween the various embodiments and/or configurations discussed. Theembodiments are not limited in their applications to the details of theorder or sequence of steps of operation of methods, or to details ofimplementation of devices, set in the description, drawings, orexamples. Moreover, individual blocks illustrated in the figures may befunctional in nature and do not necessarily correspond to discretehardware elements. While the methods disclosed herein have beendescribed and shown with reference to particular steps performed in aparticular order, it is understood that these steps may be combined,sub-divided, or reordered to form an equivalent method without departingfrom the teachings of the embodiments. Accordingly, unless specificallyindicated herein, the order and grouping of the steps is not alimitation of the embodiments. Furthermore, methods and mechanisms ofthe embodiments will sometimes be described in singular form forclarity. However, some embodiments may include multiple iterations of amethod or multiple instantiations of a mechanism unless noted otherwise.For example, when a controller or an interface are disclosed in anembodiment, the scope of the embodiment is intended to also cover theuse of multiple controllers or interfaces.

Certain features of the embodiments, which may have been, for clarity,described in the context of separate embodiments, may also be providedin various combinations in a single embodiment. Conversely, variousfeatures of the embodiments, which may have been, for brevity, describedin the context of a single embodiment, may also be provided separatelyor in any suitable sub-combination.

Embodiments described in conjunction with specific examples arepresented by way of example, and not limitation. Moreover, it is evidentthat many alternatives, modifications and variations will be apparent tothose skilled in the art. It is to be understood that other embodimentsmay be utilized and structural changes may be made without departingfrom the scope of the embodiments. Accordingly, it is intended toembrace all such alternatives, modifications and variations that fallwithin the spirit and scope of the appended claims and theirequivalents.

1) A content delivery system, comprising: several groups comprisingfractional-storage CDN servers configured to store erasure-codedfragments associated with contents; the groups are connected to theInternet via Internet backbone tier one networks, wherein not all groupsare connected via the same networks; and a very large number ofassembling devices configured to obtain fragments from sub-sets of theservers; wherein the system has a meaningful effect on the traffictransported via at least one Internet backbone tier one network bydetermining the sub-sets. 2) The content delivery system of claim 1,wherein by determining the sub-sets the system approximately avoidstransporting fragments through at least one tier one network loadedabove a predefined threshold. 3) The content delivery system of claim 1,wherein by determining the sub-sets the system shapes the fragmenttraffic via Internet backbone tier one networks, such that heavilyloaded networks are less affected than less loaded networks by thefragment traffic. 4) The content delivery system of claim 3, whereindetermining the sub-sets is done by assessing a large number ofpotential network paths that a fragment may follow from potentialservers to potential assembling devices, and preferably selecting theservers estimated to deliver fragments along the less loaded paths. 5)The content delivery system of claim 1, wherein the assembling devicesare configured to obtain a decodable number of the fragments from thesub-sets of the servers, and are further configured to decode thefragments; and the erasure-coded fragments support source-selectiondiversity. 6) The content delivery system of claim 1, wherein thecontents are streaming contents, the fragments are generated fromapproximately sequential segments of content, and the assembling devicesare located at the user premises and are configured to reconstructstreams from the obtained fragments. 7) The content delivery system ofclaim 1, wherein the erasure-coding is rateless-coding potentiallyresulting in a limitless redundancy factor; whereby high redundancyprovides greater freedom in selecting the servers from which to obtainthe fragments, and therefore better control over the fragment flowpaths. 8) The content delivery system of claim 1, wherein the assemblingdevices are configured to use a fragment pull protocol to obtain thefragments. 9) A method for shaping traffic, comprising: assessing alarge number of network paths through which erasure-coded fragmentsusually flow when transmitted from a large number of relevantfractional-storage CDN servers to an assembling device; accessingpreferences for fragment delivery via many of the paths; and selectingthe servers whose assessed paths fit well the preferences for fragmentdelivery to the assembling device; wherein the servers are accessed viathe Internet, not all servers are connected to the Internet via the samenetworks, and the erasure-coded fragments are encoded from contents andsupport source-selection diversity. 10) The method of claim 9, whereinat least some of the servers are connected to the Internet via Internetbackbone tier one networks. 11) The method of claim 10, wherein thenetwork paths consist essentially of tier one networks. 12) The methodof claim 9, wherein the network paths comprise many of the networks inthe path of a fragment delivered from a server to the assembling device.13) The method of claim 9, wherein the content is streaming content, thefragments are generated from approximately sequential segments of thecontent, and the fragments are delivered to the assembling deviceapproximately according to the sequential order of the segments. 14) Themethod of claim 9, wherein the number of network paths is at least 10,the number of relevant servers is at least 20, and the storage gain ofthe servers in regard to an average content is at least
 10. 15) Themethod of claim 9, wherein the preferences are a cost function, and thestep of selecting the servers comprises minimizing the cost function bydetermining which servers are to deliver fragments to the assemblingdevice. 16) The method of claim 9, wherein the preferences for selectinga network path are based on the accumulated costs of using the networksthrough which the path passes, whereby a lower accumulated cost resultsin a higher preference for the path. 17) The method of claim 16, whereinthe cost of delivering fragments via a network is related to the trafficload on the network, whereby the higher the traffic load on the networkthe higher the cost is, and wherein the load on the network is providedby the network operator. 18) A content delivery system, comprising: alarge number of fractional-storage CDN servers, assembling devices, anda managing component; the servers are topologically dispersed acrossdifferent Internet networks and are configured to store erasure-codedfragments associated with contents; the assembling devices areconfigured to obtain fragments from the servers; and the managingcomponent is configured to significantly affect the fragment traffictransported via at least one Internet backbone router by influencingselections of fragment delivering servers. 19) The content deliverysystem of claim 18, wherein a managing server comprises the managementcomponent, and the higher the storage gain associated with the serversand the redundancy factor associated with the contents, the higher thedegree of influence on the fragment traffic transported via the at leastone Internet backbone router. 20) The content delivery system of claim18, wherein the higher the storage gain associated with the servers andthe redundancy factor associated with the contents, the higher thedegree of influence on the fragment traffic transported via the at leastone Internet backbone router, and by selecting which of the servers touse it is possible to approximately avoid transporting fragments via atleast one Internet backbone router loaded beyond a certain level.